Patent Publication Number: US-8533266-B2

Title: User presence detection and event discovery

Description:
RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Application No. 61/598,771, filed Feb. 14, 2012, the entire content of which is incorporated herein in its entirety. 
    
    
     BACKGROUND 
     Computers and mobile devices have become increasingly interconnected due to the widespread availability of wired and wireless connections to communication networks such as the Internet. Users may share information with one another using Internet-based communications. For instance, users that are connected using Internet-based communications may share photos, messages, and other electronic resources with one another. Traditionally, a user would have to know contact information, such as an email address, phone number, social network identifier, of another user in order to share electronic resources with the other person. Obtaining such contact information may be a time consuming process or infeasible if the user wishes to share information with one or more unidentified users that share a common experience with the user. 
     SUMMARY 
     In one example, a method includes receiving, by at least one computing device, a first group of indications associated with a first group of modalities and a second group of indications associated with a second group of modalities. The first group of indications may be associated with a first remote computing device and the second group of indications is associated with a second remote computing device. The first and second groups of modalities may be usable to determine whether a first user associated with the first remote computing device is within a physical presence of a second user associated with the second remote computing device. The method also includes determining, by the at least one computing device, a confidence value for at least one modality of the first or second groups of modalities based at least in part on an indication associated with the at least one modality the indication being from the first or second group of indications. The confidence value indicates a likelihood that the first user associated with the first remote computing device is within a physical presence of the second user associated with the second remote computing device. The method also includes, upon determining that the confidence value is greater than a boundary value, performing, by the at least one computing device, an operation to indicate that the first user associated with the first remote computing device is within the physical presence of the second user associated with the second remote computing device. 
     In another example, a computing device, includes one or more processors. The computing device also includes at least one module operable by the one or more processors to: receive a first group of indications associated with a first group of modalities and a second group of indications associated with a second group of modalities. The first group of indications may be associated with a first remote computing device and the second group of indications may be associated with a second remote computing device. The first and second groups of modalities may be usable to determine whether a first user associated with the first remote computing device is within a physical presence of a second user associated with the second remote computing device. The module may be further operable to determine a confidence value for at least one modality of the first or second groups of modalities based at least in part on an indication associated with the at least one modality, the indication being from the first or second group of indications. The confidence value may indicate a likelihood that the first user associated with the first remote computing device is within a physical presence of the second user associated with the second remote computing. The module may further be operable to, upon determining that the confidence value is greater than a boundary value, determine at least one event based at least in part on a temporal identifier associated with an indication received from at least the first or second remote computing device. 
     In one example, a computer-readable storage medium may be encoded with instructions that, when executed, cause one or more processors of a first remote computing device to perform operations including: determining a group of indications associated with a group of modalities, wherein the group of modalities is associated with the first remote computing device, and wherein the group of modalities is usable to determine whether a first user associated with the first remote computing device is within a physical presence of a second user associated with the second remote computing device; sending the group of indications associated with the group of modalities to a server device to determine whether the first user associated with the first remote computing device is within a physical presence of the second user associated with the second remote computing device based at least in part on a confidence value for at least one modality of the group of modalities, wherein the confidence value is based at least in part on an indication included in the group of indications; and receiving a message from the server device that indicates whether the first user associated with the first remote computing device is within a physical presence of the second user associated with the second remote computing device. 
     The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram illustrating example client devices and a server device that may be used to determine whether users associated with computing devices are within a physical presence of one another, in accordance with one or more aspects of the present disclosure. 
         FIG. 2  is a conceptual diagram of example techniques to determine whether users associated with computing devices are within a physical presence of one another, in accordance with one or more aspects of the present disclosure. 
         FIG. 3  is a block diagram illustrating further details of one example of a server device shown in  FIG. 1 , in accordance with one or more aspects of the present disclosure. 
         FIG. 4  is an example of a computing device displaying a graphical user interface, in accordance with one or more aspects of the present disclosure. 
         FIG. 5  is an example of a computing device displaying a graphical user interface, in accordance with one or more aspects of the present disclosure. 
         FIG. 6  is a flow diagram illustrating example operations of a computing device to determine whether users associated with computing devices are within a physical presence of one another, in accordance with one or more aspects of this disclosure. 
         FIG. 7  is a flow diagram illustrating example operations of a computing device to determine whether users associated with computing devices are within a physical presence of one another, in accordance with one or more aspects of this disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In general, this disclosure is directed to techniques that may use information from a diverse group of modalities to determine whether two or more individuals are in physical proximity to one another, and in some instances, whether the individuals may be associated with the same event. For instance, example modalities may include geo-location, audio-fingerprinting, proximity detection, and calendar data. Each modality may provide some information about the proximity of one individual to another. In some examples, modalities may further indicate an event which may be associated with the individuals. Under different circumstances, different modalities may provide more or less precise information that indicates if individuals are in a physical presence of one another. 
     In one example, multiple users may be in a physical presence of one another. Moreover, each user may have a mobile computing device such as a smartphone. Each smartphone may provide information associated with one or more modalities to a remote server implementing techniques of the present disclosure. For instance, each smartphone may send information that includes a geoposition of the smartphone and an audio fingerprint that represents a sample of sound received by the smartphone. Using techniques of the present disclosure, the remote server may receive such information associated with the one or more modalities. The remote server may, for information received from each phone, determine the quality and/or margin of error of information associated with each modality. Using techniques of the disclosure, the remote server may weigh the information associated with each modality based at least in part on the quality and/or margin of error of the information. The remote server may determine a confidence value (e.g., a likelihood) that the users associated with the smartphones are within a physical presence one another based on the weighted information associated with the modalities of each smartphone. If the remote server determines, using the using the confidence value, that the users are within a physical presence one another, the remote server may perform additional operations, such as notifying the users of their physical proximity to one another and/or determining whether the users are associated with a common event. By determining that users are in physical proximity and associated with a common event, techniques of the present disclosure may enable users to establish relationships more easily and share content, e.g., using a social networking service, with less effort. 
       FIG. 1  is a block diagram illustrating example client devices  4 A- 4 C (collectively referred to as “computing devices  4 ”) and a server device  22  that may be used to determine the proximity of the client devices to one another, in accordance with one or more techniques of the present disclosure. In some examples, each of computing devices  4  may be referred to as a remote computing device. Computing devices  4  may be associated with users  2 A- 2 C (collectively referred to as users  2 ). For instance, a user associated with a computing device may interact with the computing device by providing various user inputs to interact with the computing device. In some examples, a user may have one or more accounts with one or more services, such as a social networking service and/or telephone service, and the accounts may be registered with the computing device that is associated with the user. As shown in  FIG. 1 , user  2 A is associated with computing device  4 A, user  2 B is associated with computing device  4 B, and user  2 C is associated with computing device  4 C. 
     Computing devices  4  may include, but are not limited to, portable or mobile devices such as mobile phones (including smart phones), laptop computers, desktop computers, tablet computers, and personal digital assistants (PDAs). Computing devices  4  may be the same or different types of devices. For example, computing device  4 A and computing device  4 B may both be mobile phones. In another example, computing device  4 A may be a mobile phone and computing device  4 B may be a tablet computer. 
     As shown in  FIG. 1 , computing device  4 A includes a communication module  6 A, input device  8 A, output device  10 A, short-range communication device  12 A, and GPS device  13 A. Other examples of a computing device may include additional components not shown in  FIG. 1 . Computing device  4 B includes a communication module  6 B, input device  8 B, output device  10 B, short-range communication device  12 B, and GPS device  13 B. Computing device  4 C includes a communication module  6 C, input device  8 C, output device  10 C, short-range communication device  12 C, and GPS device  13 C. 
     Computing device  4 A may include input device  6 A. In some examples, input device  6 A is configured to receive tactile, audio, or visual input. Examples of input device  6 A may include a touch-sensitive and/or a presence-sensitive screen, mouse, keyboard, voice responsive system, microphone, camera or any other type of device for receiving input. Computing device  4 A may also include output device  10 A. In some examples, output device  10 A may be configured to provide tactile, audio, or video output. Output device  10 A, in one example, includes a touch-sensitive display, sound card, video graphics adapter card, or any other type of device for converting a signal into a form understandable to humans or machines. Output device  10 A may output content such as graphical user interface (GUI)  16  for display. Components of computing devices  4 B and  4 C may include similar or the same functionality as described with respect to components of computing device  4 A. In some examples, components of computing devices  4 B and  4 C may include functionality that is different from computing device  4 A. 
     As shown in  FIG. 1 , computing device  4 A includes a short-range wireless communication device  12 A. In one example, short-range wireless communication device  12 A is capable of short-range wireless communication  40  using a protocol, such as Bluetooth or Near-Field Communication. In one example, short-range wireless communication  40  may include a short-range wireless communication channel. Short-range wireless communication  40 , in some examples, includes wireless communication between computing devices  4 A and  4 B of approximately 100 meters or less. Computing devices  4 B and  4 C may include short-range communication devices  12 B and  12 C, respectively, with functionality that is similar to or the same as short-range communication device  12 A. 
     Computing devices  4 A- 4 C may also include Global Positioning System (GPS) devices  13 A- 13 C (collectively referred to as GPS devices  13 ), respectively. GPS devices  13  may communicate with one or more GPS sources, such as GPS source  42 , to obtain geopositions of each respective computing device. GPS source  42  may be a GPS satellite that provides data usable to determine a geoposition. A geoposition may include, for example, coordinates that identify a physical location of the computing device in a GPS mapping system. For instance, a geoposition may include a latitude coordinate and a longitude coordinate of the current physical location of a computing device. 
     As shown in  FIG. 1 , server device  22  may include proximity module  24 , event module  26 , logging module  28 , visualization module  30 , social networking module  32 , event data  34 , logging data  36 , and user data  38 . Computing devices  4  and server device  22  may be operatively coupled by communication channels  40 A- 40 D, which in some examples may be wired or wireless communication channels capable of sending and receiving data. Examples of communication channels  40 A- 40 D may include Transmission Control Protocol/Internet Protocol (TCP/IP) connection over the Internet or 3G wireless network connection. Network  14  as shown in  FIG. 1  may be any network such as the Internet, or local area network (LAN). 
     Users  2 A,  2 B,  2 C as shown in  FIG. 1  may have various shared experiences with one another in different environments. For instance, user  2 A may be in physical proximity with user  2 B in an environment such that the users may carry on a conversation (e.g., users  2 A and  2 B are sitting together at a coffee shop). In other examples, user  2 A may be in an environment with many different users (e.g., user  2 A attends a wedding or conference). In any case, user  2 A may wish to easily share content and establish relationships with other users participating in the same shared experience (e.g., the meeting at the coffee shop or the wedding). User  2 A may not have the ability easily establish a relationship with other users participating in the shared experience because conventional methods of establishing relationships with other users may require user effort that detracts from participation in the shared experience. Such experiences may prevent or discourage users from quickly and easily sharing content associated with the shared experience. 
     Techniques of the present disclosure may enable a user participating in a shared experience, such as a common event or being within a physical presence of another user, to determine that other users are participating in the same experience. In some examples, techniques of the disclosure may also improve the ease of connecting with and establishing relationships with other users participating in a shared experience. The techniques may also reduce user effort to share and receive content associated with the shared experience. In this way, techniques of the present disclosure may improve a user&#39;s ability to determine who the user is spending time with and what activities the user is engaged in. Techniques of the disclosure may reduce user effort to establish relationships with other user in some examples by automatically determining who a user has spent time with. Techniques of the disclosure may also enable a user to determine who they spent their time with, where they&#39;ve spent their time, and what activities they were engaged in. 
     To identify shared experiences, techniques of the present disclosure may determine whether computing devices associated with users are in proximity to one another based on one or more modalities. A modality, generally, may be any source of information usable to determine whether computing devices are in proximity to one another. By comparing information from various modalities associated with each computing device, techniques of the present disclosure may determine that computing devices, and therefore the users associated with the computing devices, are in physical proximity to one another. The techniques may further determine that users in physical proximity to one another are participating in a shared experience (e.g., an event). Upon determining that users are participating in a shared experience, techniques of the disclosure may, for example, notify the users of the shared experience, enable users to establish relationships with other users, share content associated with shared experience, etc. 
     Referring to  FIG. 1 , techniques of the present disclosure will now be described with respect to computing devices  4 A,  4 B,  4 C and server device  22 . Computing devices  4 A- 4 C may include communication modules  6 A- 6 C. Communication modules  6 A- 6 C may be implemented in hardware, software, or a combination thereof. Each of communications modules  6 B- 6 C may have similar or the same functionality as communication module  6 A described herein. 
     As shown in  FIG. 1 , communication module  6 A may generate one or more indications associated with one or more modalities. For instance, communication module  6 A may receive information associated with each modality and generate one or more indications based on the information. Example modalities may include a short-range communication modality, a geoposition (or GPS) modality, an audio source modality, a visual source modality, a calendaring source modality, a check-in source modality, and a network identifier modality. Many other sources of information usable to determine that one computing device is in proximity to another computing device are contemplated within the scope of this disclosure and the modalities described herein should not be understood as an exclusive group of modalities. An indication generated by a communication module and associated with a modality may be data that include information usable to determine whether the computing device that includes the communication module is in physical proximity to another computing device. Computing device  4 A may send indications associated with modalities to server device  22 . 
     In one example of generating indications associated with a modality (e.g., short-range wireless communication), communication module  6 A may receive information from short-range wireless communication device  12 A that computing device  4 A has detected computing device  4 B using short-range wireless communication. For instance, communication module  6 A may receive an identifier of computing device  4 B. Alternatively, communication module  6 A may receive an identifier that identifiers user  6 B, such as a user identifier in a social networking service or information from a vCard such as a name, address, phone number, email address, etc. In any case, communication module  6 A may generate one or more indications that indicate computing device  4 A has detected computing device  4 B and/or user  2 B using short-range wireless communication. The indications may further include information that indicates the strength of the short-range wireless communication channel between computing device  4 A and computing device  4 B. In some examples, the indications may include information that indicates the distance between computing device  4 A and computing device  4 B. 
     In another example of generating indications associated with a modality, communication module  6 A may receive information from GPS device  13 A that indicates a geoposition of computing device  4 A. As previously described, a geoposition may indicate one or more coordinates that identify a physical location of computing device  4 A. Communication module  6 A may generate one or more indications that include geographic identifiers that identify the geoposition of computing device  4 A. The indications may further indicate the strength of the communication between GPS device  13 A and GPS source  42 . In some examples, the indications may indicate the precision or margin of error associated with the geoposition. In one example, geoposition information that includes the geoposition may be associated with an indication generated by communication module  6 A. 
     Communication module  6 A may also use modalities including audio and visual sources to generate indications. For instance, communications module  6 A may capture ambient audio and/or video signals in an environment surrounding computing device  4 A. In one example, input device  8 A may be a microphone that receives audio signals, which are then used by communication module  6 A to generate indications representing the audio signals. Similarly, in some examples, input device  8 A may be a camera that can capture visual signals, which communication module  6 A may use to generate indications representing the visual signals. In some examples, additional information such as the quality of the audio and/or visual signals may be included in the indications. 
     In the example shown in  FIG. 1 , each of computing devices  4  may send indications associated with various modalities to service device  22 . In some examples, each of computing devices  4  may be associated with a unique identifier that identifies the computing device. In the example of computing device  4 A, communication module  6 A may associate the unique identifier of the computing device with indications that are sent by computing device  4 A to server device  22 . In this way, server device  22  may determine the identity of each computing device associated with a particular indication. 
     As shown in  FIG. 1 , server device  22  may receive a first group of one or more indications associated with modalities from computing device  4 A. Server device  22  may also receive second and third groups of modalities from computing devices  4 B and  4 C. In some examples, server device  22  may continuously receive indications from computing devices according to a time interval or as the indications are generated and sent by the computing devices. As previously described, the modalities and corresponding indications may be usable to determine whether, for example, the users  2 A and  2 B that are associated with computing devices  4 A and  4 B within a physical presence of one another. 
     In some examples, user  2 A may be in a physical presence of user  2 B when the users are able to physically communicate with one another using speech or sign language. For instance, user  2 A may be in a physical presence of user  2 B when user  2 A is near user  2 B such that user  2 A can speak or engage in sign language with user  2 B without the assistance of wireless communication enabled by computing devices. In some examples, user  2 A may be within a physical presence of user  2 B when the users are within a predetermined distance. In one example, user  2 A may be in the physical presence of user  2 B when user  2 A is within a 0-5 meter radius of user  2 B. In a different example, user  2 B may be in a physical presence of user  2 B when user  2 B is within a 0-20 meter distance. As described herein, techniques of the present disclosure may determine that two or more users are in a physical presence of one another based on multiple, different types of indications that indicate users are engaged in a common social experience including, but not limited to, for example, physical distance, social networking information, event information, etc. Because users  2 A and  2 B may interact with and/or carry computing devices  4 A and  4 B on his/her persons, respectively, techniques of the present disclosure may determine that two or more users are in a physical presence of one another using the indications of the computing devices and, in some examples, other sources of information. 
     Proximity module  24  may implement techniques of the present disclosure to determine whether computing devices are in proximity to one another and consequently determine whether users are in a physical presence of one another. Initially, proximity module  24  may receive indications associated with modalities from computing devices, such as computing devices  4 . In some examples, proximity module  24  may determine the unique identifier of the computing device associated with the indication. Upon receiving an indication, proximity module  24  may determine a confidence value for the modality associated with the indication. The confidence value may represent a likelihood that the modality indicates whether, for example, computing device  4 A is physically located within a physical presence  38  of computing device  4 B. In some examples, a confidence value may be one or more probabilities or other determined values that indicate a likelihood that a modality indicates users of two or more computing devices are within a physical presence of one another. 
     In accordance with techniques of the disclosure, a confidence value may be based at least in part on the quality and/or precision of the information associated with a modality when determining whether computing devices are in proximity to one another. For instance confidence values may be based on a spectrum of margins of error associated with a modality. For example, as the margin of error for the geoposition increases, the confidence value generated by proximity module  24  for the GPS modality may decrease. Similarly, as the margin of error for the geoposition decreases, the confidence value generated by proximity module  24  may increase. As further described herein, a GPS indication may include a geoposition of computing device  4 A and a margin of error for the geoposition, i.e., +/−3 meters (e.g., if computing device  4 A is outdoors with an unobstructed path to GPS source  42 ). In another example, a GPS indication may indicate a margin of error of +/−50 meters (e.g., if computing device  4 A is in a building with an obstructed path to GPS source  42 ). By generating a confidence value using quality and/or precision information, techniques of the present disclosure may provide more precise determinations of whether users associated with two or more computing devices are within a physical presence of one another. 
     Although the previous example illustrated the use of distance as a margin of error for a GPS modality, any suitable margin of error for GPS may be used. Moreover, indications for other modalities may also include quality and/or margin of error information. For instance, indications of a visual modality may include a resolution, indications of an audio modality may include a frequency range or bit rate, indications of short-range wireless communication may include a distance or signal strength, etc. 
     Referring now to the example of  FIG. 1 , proximity module  24  may use indications associated with one or more modalities of computing devices to improve the precision of determining whether users associated with computing devices are within a physical presence of one another. For instance, computing devices  4 A and  4 B may each send indications associated with GPS, audio source, and short-range wireless communication modalities. As one example, communication module  6 A may send indications that include geopositions based on information received from GPS source  42 . Communication module  44  may also generate indications based on ambient audio from audio sources  44  using audio signals received from input device  8 A. Using short-range wireless communication device  12 A, communication module  6 A may also generate an indication that includes an identifier of computing device  4 B. Communication module  6 B may similarly generate indications for the GPS, audio source and short-range wireless communication modalities. Communication modules  6 A and  6 B may each send the indications to server device  22 . 
     Proximity module  24  may initially receive the indications from server device  22 . As will be further described in the examples of  FIGS. 1 and 2 , proximity module  24  may use indications associated with various modalities from one or more computing devices to determine a confidence value for at least one modality that indicates a likelihood that the at least one modality indicates whether user  2 A of computing devices  4 A is within physical presence  38  of user  4 B. In some examples, proximity module  24  may use margin of error and/or quality information included in the indications to generate the confidence values associated with the various modalities to more precisely determine whether two users of computing devices are within a physical presence of one another. For instance, proximity module  24  may generate a larger confidence value (e.g., indicating a higher likelihood two devices are within a determined distance) for modalities and indications that have higher quality and lower margins of errors. Proximity module  24  may also may generate a smaller confidence value (e.g., indicating a lower likelihood two devices are within a determined distance) for modalities and indications that have lower quality and higher margins of errors. 
     Referring to the example of  FIG. 1 , proximity module  24  may determine a confidence value (e.g., a probability) using geopositions of computing devices  4 A and  4 B that indicate users  2 A and  2 B are within a physical presence of one another. For example, proximity module  24  may determine the margins of error associated with the geopositions received from the computing devices. By comparing the distance between the geopositions of computing device  4 A and  4 B, and applying the margins of error associated with the geopositions, proximity module  24  may determine the probability that computing devices  4 A and  4 B are within a predetermined distance. Generally, increases in the margin of error and distance between the geopositions may result in a lower probability that computing devices  4 A and  4 B are within the predetermined distance while decreases in the margin of error and distance between the geopositions may result in a higher probability that the devices are within the predetermined distance. 
     Proximity module  24  may also compare indications associated with audio sources that are received from computing devices  4 A and  4 B to determine a confidence value that indicates whether users  2 A and  2 B are within a physical presence of one another. Audio indications may include one or more audio fingerprints, which may identify and/or represent audio signals received by input devices  8  of computing devices  4 . In one example, proximity module  24  may perform one or more audio recognition techniques (e.g., audio fingerprinting) to determine a probability that audio indications match. For instance, proximity module  24  may determine a degree of similarity between at least one first audio fingerprint associated with computing device  4 A and at least one audio fingerprint received from the computing device  4 B. The degree of similarity may be within a range of degrees of similarity. Proximity module  24  may also generate the confidence value based at least in part on quality and/or margin of error information for the audio indications. For example, proximity module  24  may generate lower confidence values for the audio modality when the quality of the audio indications is low. Quality and/or margin of effort information may include a bit rate, frequency range, level of background noise, etc., associated with the audio indications. 
     Proximity module  24  may also compare identifiers of computing devices  4 A and  4 B obtained by the respective devices using short-range wireless communication, to determine a confidence value that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. For instance, computing device  4 A may send indications to server device  22  that include an identifier of computing device  4 A and an identifier of computing device  4 B that was received by computing device  4 A using short-range wireless communication. Similarly, computing device  4 B may send indications to server device  22  that include an identifier of computing device  4 B and an identifier of computing device  4 A that was received by computing device  4 B using short-range wireless communication. By comparing the similarity, for example, between the identifiers of computing device  4 A that are received by server device  22 , proximity module  24  may determine the probability that the identifiers match, thereby indicating whether the computing devices are within proximity to one another. Proximity module  24  may generate the confidence value based in part on quality and/or margin of error information. Such information may include signal strength of the short-range wireless communication between computing devices  4 A and  4 B. 
     Upon generating confidence values for each of the modalities (e.g., GPS, audio, short-range wireless communication) associated with indications, proximity module  24  may determine that the computing devices  4 A and  4 B are within physical presence  38  of one another. For instance, as further described in  FIG. 2 , proximity module  24  may weight each of the modalities by applying the confidence values to the indications associated with each of the respective modalities. In one example, proximity module  24  may sum the confidence values and determine if the sum is greater than a predefined value. If the sum is greater than the predefined value, proximity module  24  may determine that users  2 A and  2 B of computing devices  4 A and  4 B are within a physical presence  38  of one another. In another example, proximity module  24  may determine whether each confidence value is greater than a corresponding predefined value. If a confidence value associated with a modality is less than a corresponding predefined value, proximity module  24  may ignore the confidence value associated with the modality. Consequently, in such examples, only confidence values that are greater than corresponding predefined values are used by proximity module  24  to determine whether users  2 A and  2 B are within a physical presence  38  of one another. Further techniques for using the confidence values are described with reference to  FIG. 2 . 
     The previous example illustrated the use of indications associated with modalities that were received by proximity module  24  from computing devices  4 A and  4 B. Proximity module  24  may also use indications from other modalities. Other such modalities may include a calendar service, social network service, and/or network accessible documents. Network accessible documents may include, for example, any file accessible on a network such as the Internet. Example network accessible documents may include HTML files, word processing files, spreadsheets, media files, etc. For example, proximity module  24  may query one or more calendar services. User  2 A and user  2 B may use calendar services that enable the users to schedule events at various dates and times. Proximity module  24 , in some examples, may query the calendaring services to determine calendar events for users  2 A and  2 B. For instance, proximity module  24  may initially determine a current date and time associated with computing devices  4 A and  4 B. Using the date and time, proximity module  24  may determine calendar events for user  2 A and  2 B in the calendar services. Each calendar event may include event information (e.g., indications) such as, a date, start and end time, location, event description, participants etc. In one example, proximity module  24  may compare event information for calendar events of users  2 A and  2 B that occur at the current date and time to determine similarities between the event information. 
     Based on a degree of similarity between information associated with the calendar events, proximity module  24  may determine a confidence value (e.g., a probability) for the calendar modality based at least in part on the event information of user  2 A and  2 B. For instance, if proximity module  24  determines a high degree of similarity between the locations, start/end times, and start/end dates, proximity module  24  may generate a confidence value that indicates a high likelihood that users  2 A and  2 B associated with computing device  4 A and  4 B are within a physical presence of one another. 
     As another modality, proximity module  24  may use social networking data  38  (e.g., indications). Social networking data  38  may include data used in a social networking service. As shown in  FIG. 1 , social networking module  32  may provide a social networking service in which users  2  each generate corresponding user accounts. Social networking data  38  may include data that indicates relationships between users  2  in the social networking service. Social networking data  38  may also include user profile information associated with users  2 , event information associated with events, content (e.g., text, videos, photographs, etc.) or any other data used by a social networking service. In one example, user  2 A may provide a status update in the social networking service that indicates a location and time of user  2 A. Similarly, user  2 B may also provide a status update that includes information about a time and location of user  2 B. Proximity module  24  may compare the status update information and determine a confidence value that indicates whether user  2 A and  2 B associated with computing device  4 A and  4 B are within a physical presence of one another based on the similarities between the location and time information. Although described using status updates, date, time, and location information, any suitable social networking data  38  may be used by proximity module  24 . Still other example modalities may include network addresses (e.g., Internet protocol addresses) of computing devices  4  and check-in services that indicate locations where users  2  have checked in. Such modalities may similarly be used by proximity module  24  to determine whether users  2 A and  2 B of computing devices  4 A and  4 B are within a physical presence of one another. 
     In some examples, proximity module  24  may compare the confidence value to a boundary value to determine whether users associated with computing devices are within a physical presence of one another. A boundary value may be any value by a user or automatically generated by a computing device. In some examples, if the confidence value is greater than a boundary value, server device  22  may perform one or more operations to indicate that users associated with computing devices are within a physical presence of one another. Although illustrated as a comparison of a confidence value that is greater than a boundary value, any suitable comparison may be performed between a confidence value and a boundary value to determine whether users associated with computing devices are within a physical presence of one another. 
     Upon determining that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another, server device  22  may perform one or more operations to indicate that the users are within the physical presence of one another. For instance, event module  26  may send one or more messages that include information for display to computing devices  4 A and  4 B that indicate users  2 A and  2 B associated with computing devices are within a physical presence of one another. The information may identify computing device  4 B and/or user  2 B. For example, the information may include data from user  2 B&#39;s social network profile, such as a name, photo, email address, username, etc. In one example, communication module  6 A upon receiving such a message may cause output device  10 A to display at least some of the information in graphical user interface (GUI)  16 . As shown in  FIG. 1 , GUI  16  may display information  20 A indicates user  2 B is within a physical presence of user  2 A. In some examples, GUI may further include user interface objects  18 A. User interface objects  18 A may be control buttons, although any suitable user interface components may be used. 
     User interface objects  18 A may be selectable by user  2 A via input device  8 A and/or output device  10 A. For instance, user  2 A may provide a user input to confirm whether user  2 B is within a physical presence of user  2 A by selecting the “Y” (e.g., yes) user interface component of user interface components  18 A. Upon determining user  2 A has provided a user input, communication module  6 A may send a message to server device  22  to indicate the selection. Upon receiving the message, logging module  28  may store log data  36  to indicate that user  2 A and user  2 B are within a physical presence of one another. Logging module  28  and log data  36  are further described in the example of  FIG. 4 . In some examples, server device  22  may generate a mailing list, social group in a social networking service, or follow-up event in response to determining users associated with computing devices are within a physical presence of one another. 
     In another example, event module  26  may perform an operation to indicate computing devices  4 A and  4 B that includes determining a current time associated with computing device  4 A, computing device  4 B, and/or server device  22 . The current time may be a date and time associated with one of the devices when proximity module  24  determines whether computing devices  4 A and  4 B are in proximity to one another. In another example, the current time may be a date and time associated with indications received by server device  22  from computing devices  4 A and  4 B. For instance, a temporal identifier in an indication sent by computing device  4  to proximity module  24  may include a current date and time. 
     In any case, upon determining the current time, event module  26  may determine at least one event based at least in part on the temporal identifier. For instance, event module  26  may query event data  34  using the temporal identifier to determine one or more events. Event data  34  may be stored in one or more event data sources, which may include databases, caches, documents, or any other suitable data storage structure. Examples of event data  34  may include event data in a calendaring system, information stored on Internet pages, or any other source of event information. Further examples of event data  34  may include, document, calendar system, web page, email, instant message, and text message. Event module  26  may also query social networking data  38  to determine the event. An event, generally, may be any gathering, happening, or other observable occurrence. Examples of events may include a meeting, party, concert, wedding, gathering, occurrence that includes zero or more people, etc. Event module  26  may query event data  34  and social networking data  38  using the temporal identifier to identify events that overlap with or occur within specified time duration of the date and/or time specified by the temporal identifier. For instance, calendar events included in calendars of calendaring services for users  2 A and  2 B may indicate start time, end time, location, event description and other suitable event information. 
     Event module  26  may determine that a start time of an event for user  2 A&#39;s calendar overlaps with an end time for user  2 B&#39;s calendar. Consequently, because event module  26  has determined that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence  38  of one another and that calendar events associated with calendars of user  2 A and  2 B overlap, event module  26  may send a message to computing devices  4 A and  4 B that includes information for display at the computing devices to indicate the event. For instance, if the calendar event associated with user  2 A indicated “Jake&#39;s Wedding” and the calendar event associated with user  2 B indicated “Chelsea&#39;s Wedding,” event module  26  may send a message to computing device  4 A that displays information  20 B, e.g., “You appear to be at Chelsea&#39;s Wedding.” User  2 A may select a user interface object “Y” (e.g., Yes) of user interface objects  18 B to indicate user  2 A is attending Chelsea and Jake&#39;s wedding. Communication module  6 A may send a message to server device  22  to indicate the selection. In some examples, event module  26 , upon receiving the message may associate user  2 A with an event in event data  34  that represents Chelsea and Jake&#39;s wedding. The message, in some examples, may include one or more characteristics that describe the event. For instance, characteristics may include an event name, event time/date, event participants, event media (e.g., photos, videos, audio, etc.), or any other descriptive information about the event. Logging module  28 , in response to receiving the message, may also store data that indicates user  2 A is attending Chelsea and Jake&#39;s wedding. Logging module  38  may, in some examples, store data in logging data  36  that indicates user  2 A was within a physical presence  38  of user  2 B. 
     In some examples, event module  26 , may determine an event based at least in part on a temporal identifier that includes a current date and time and further based at least in part on geopositions associated with indications received from computing devices  4 A and  4 B. For instance, event module  26  may determine an event by querying event data  34  using geopositions of computing devices  4 A and  4 B and temporal identifier. Event module  26  may determine one or more events are indicated in event data  34  that are associated with or near geopositions of computing devices  4 A and  4 B, and further overlap in time with the temporal identifier. In some examples, event module  26  may use geoposition coordinates to identify a geographic area rather than a precise location to provide greater flexibility in identifying events that match the geopositions of computing devices  4 A and  4 B. 
     When event module  26  has determined one or more events based at least in part on one of the geoposition data and/or temporal identifier, event module  26  may send one or more messages to computing devices  4 A and  4 B that include information for display at the computing devices. The message may include information that indicate the events determined by event module  26  based at least in part on geoposition data and/or temporal identifier. Communication module  6 A may cause output device  10 A to display user interface objects that user  2 A may select to indicate whether user  2 A is attending the events. Upon determining user  2 A has provided a user input to select one or more of the user interface objects, communication module  6 A may send one or more messages to server device  22 . Event module  26  may store data in event data  34  to indicate user  2 A is associated with the one or more selected events indicated by the messages. Logging module  36  may store data in logging data  36  to similarly indicate that user  2 A has attended the event. 
     In some examples, event module  26  may determine spontaneously, e.g., on an ad hoc basis whether an event is occurring based on whether users associated with computing devices are within a physical presence of one another. For instance, event module  26 , upon determining users  2 A and  2 B are within a physical presence of one another, may further determine whether an event is indicated in event data  34  and/or social data  38  based at least in part on one of a temporal identifier or geoposition. If event module  26  does not determine an event, event module  26  may determine whether to generate data in event data  34  that indicates an event based on one or more event criteria (e.g., event module  26  may determine the event and generate the event data on an ad hoc basis). For instance, a criterion may be based on a distance between computing devices, a frequency with which users associated with computing devices are within a physical presence of one another at an indicated time, a density of computing devices within a predetermined area, whether a relationship exists in a social networking service between users, or any other suitable criteria to determine an event has occurred. 
     In one example of determining a criterion, users  2 A and  2 B may meet in the same geographic location according to regular interval (e.g., a regular meeting at a particular time and day). Event module  26  may include a criterion that an event is determined to exist when two users are within a geographic area at a regular interval. Consequently, event module  26  may determine the criterion is satisfied and generate data in event data  34  that indicates the event. Event module  26  may send messages to computing devices  4 A and  4 B to indicate the event. Such message may be used to enable users  2 A and  2 B to confirm the existence of the event. Event module  26  may subsequently receive messages based on input from users  4 A and  4 B from computing devices  4 A and  4 B which may be used to confirm the event in event data  43 . Event module  26  may for example associate users  2 A and  2 B with event data in event data  34 . Although a single criterion has been described, any number of criteria may be used in combination or separately to determine when an event may be generated in response to determining that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. 
     In some examples, techniques of the present disclosure may improve the accuracy of determining whether an event is occurring spontaneously and on an ad hoc basis using negative information. Negative information, generally, may be data usable to determine that event is not occurring or does not exist. In this way, routine occurrences or occurrences that are not of suitable significance may not be determined by event module  26  to be events. For instance, negative information may indicate that user  2 A is at single location for an extended period of time (e.g., his or her workspace) that within a predetermined distance of user  2 B who is also at a single location for an extended period of time. Consequently, proximity module  24  may determine that user  2 A and  2 B are not attending a spontaneous event because the location of user  2 A and user  2 B (and corresponding devices  4 A and  4 B) routinely in this same physical area for the same time. Thus, proximity module  24 , in some examples, may use indications associated with various modalities to determine events are not occurring. In another example, users  2 A and  2 B may be attending an event together (e.g., having coffee at a coffee shop). User  2 C may be within a predetermined distance from user  2 A and  2 B at the event; however, proximity module  24  may determine that user  2 C does not have relationships with users  2 A and  2 B in a social networking service. Consequently, proximity module  24  may determine that user  2 C is not attending the event of users  2 A and  2 B. Thus, proximity module  24  may not send a message, for example, to indicate the event of user  2 A and  2 B. While the previous examples provide two illustrations of using negative information to determine a user is not associated with an event, negative information may be used in any variety of ways to improve the accuracy of determining whether an event is occurring and which users are associated with such an event. 
     As another example of performing an operation to indicate that computing devices  4 A and  4 B are within a physical presence of one another, event module  26  may generate an event page associated with an event as further described in  FIG. 5 . In some examples, proximity module  24 , upon determining that users  2 A and  2 B of computing devices  4 A and  4 B are within a physical presence of one another, may send messages the computing devices that enable users  2 A and  2 B to engage in a group chat. 
     In still another example of performing an operation to indicate that computing devices  4 A and  4 B are within a physical presence of one another, social networking module  32 , in response to determining an event, may generate a social group in a social networking service that is associated with the event. A social group may be a group of one or more users in a social networking service that are associated with an event. In some examples, content associated with the event (e.g., content shared on an event page) may be created, accessed by, and/or modified by users included in the social group. In such examples, social networking module  32  may, in response to determining the event, send a request to computing device  4 A to associate user  2 A with a social group corresponding to the event. Communication module  6 A may cause output device  10 A to display a prompt to user  2 A that enables user  2 A to associate with or not associate with the social group. Upon receiving a selection from the user, communication module  6 A may send a message to social networking module  32  to associate or not associate user  2 A with the social group in the social networking service. 
     In some examples, techniques of the present disclose may enable users to transitively establish relationships in a social network when computing devices of the users are within a predetermined distance of one another. In other examples, techniques of the present disclosure may enable a third user to receive a notification of an event from a first user when each of the first and third users a relationship with a second user in a social networking service. For example, as shown in  FIG. 1 , upon receiving indications from computing devices  4 A- 4 B, proximity module  24  may determine that computing device  4 C is within a predetermined distance from computing device  4 B. Upon determining computing devices  4 B and  4 B are within the predetermined distance, social networking module  32  may determine whether relationships exist between user  2 C and one or both of users  2 A and/or  2 B. If social networking module  32  determines that a relationship exists between user  2 C and one or both of users  2 A and  2 B, event module  26  may further determine whether users  2 A and  2 B are participating in an event. For instance, event module  26  may determine that computing devices  4 A and  4 B are within a predetermined distance and further the location of computing device  4 A or  4 B is within an area that includes an event. If such an event exists, event module  26  may send a message to computing device  4 C that indicates the event. In this way, computing device  4 C may receive an indication of an event attended by users  2 A and  2 B when user  2 C is within a predetermined distance from one or both of users  2 A and  2 B. 
     The aforementioned techniques may be implemented by server device  22  to enable user  2 C to transitively establish relationships in a social networking service with other users and suggest possible relationships to other users. For instance, if computing devices  4 A and  4 B are within predetermined distance  38  of each other, social networking module  32  may determine if user  2 A has a relationship with user  2 C in a social networking service. If so, event module  26  may send a message to computing device  4 C that indicates user information of user  2 B. Thus, when a relationship exists between user  2 A and  2 C, server device  22  may send a message to computing device  4 B to indicate a potential relationship between user  2 B and user  2 C. Consequently, user  2 C may add user  2 B to user  2 C&#39;s social network. In some examples, user  2 C may receive a request to confirm that user  2 B and user  2 C are or have attended an event together or were within a predetermined distance. In this way, techniques of the disclosure may query social networks of a user  2 A who is within a predetermined distance of user  2 B and notify user  2 C of user  2 B because user  2 A and user  2 C have a relationship in a social networking service. In some examples, computing device  4 C may receive a notification that enables user  2 C to establish a relationship with user  2 B in the social networking service. A predetermined distance may be any value indicating a distance that is input by a user or generated by a computing device. 
     Techniques of the present disclosure may be performed as computing devices send indications to server device  22 , as previously described in  FIG. 1 . In such examples, server device  22  may process current indications to perform techniques of the present disclosure as new indications are received (e.g., as computing devices  4 A and  4 B enter into a predetermined distance). In other examples, techniques of the present disclosure may determine, at a later time that users associated with computing devices were within a physical presence of one another at a previous time. For instance, techniques of the disclosure may evaluate one or more indications any time after the indications are received to determine, e.g., whether two computing devices are within a predetermined distance of one another or users are participating in an event. 
       FIG. 2  is a conceptual diagram of techniques to determine whether users associated with computing devices are within a physical presence of one another, in accordance with techniques of the present disclosure. As shown in  FIG. 2 , computing devices  4 A and  4 B may send indications associated with modalities to a server device that includes proximity module  24  as described in  FIG. 1 . As shown in  FIG. 2 , proximity module  24  may make a single decision (e.g., computing devices in proximity, yes or no) given information from diverse modalities. In the example of  FIG. 2 , each modality is represented by an agent component. For instance, GPS agent  60 , Bluetooth agent  62 , and audio recognition agent  64  may receive, respectively: geoposition indications, short-range wireless communication indications, and audio indications from computing devices  4 A and  4 B. As will be further describe with respect to  FIG. 2 , mixer  66  may use confidence values from the agents to determine whether users associated with computing devices are within a physical presence of one another. Because different modalities will fail under different circumstances, mixer  66  may make well informed decisions by providing greater weight to agents with low margin of error and high quality sources (e.g., more trustworthy agents) and lesser weight to less trustworthy sources. 
     As shown in  FIG. 2 , mixer  66 , implementing techniques of the disclosure may determine whether computing devices  4 A and  4 B are in proximity to one another, e.g., whether users associated with computing devices  4 A and  4 B are within a physical presence of one another. Each of computing devices  4 A and  4 B may have access to a GPS and the Bluetooth stack. In some examples, each of these modalities may independently be sufficient for mixer  66  to make a determination as to whether users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. In other circumstances, mixer  66  may use multiple modalities to make the determination. To provide more precise determinations about the proximity of computing devices  4 A and  4 B to one another, agents may determine confidences in indications received from the computing devices in different circumstances. Agents  60 - 64  may derive a measure of confidence from the indications themselves. For instance, GPS indications may provide explicit uncertainty bounds (e.g., margin of error) along with a geoposition. Bluetooth scans provide an implicit measure of uncertainty in that a short-range wireless communication via Bluetooth may detect many or few other computing devices. 
     As one example, computing devices  4 A and  4 B may be at a high altitude with few obstructions, e.g., at the top of a mountain. The computing devices will get good signals from many satellites and the position uncertainty may be very low. In such examples, mixer  68  may determine whether users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another based solely on GPS. In the current example, there may be few other Bluetooth sources: possibly only one other computing device on another mountaintop nearby. Seeing the Bluetooth signal of this other computing device may or may not be a useful indication of proximity since very low radio frequency noise will be present and the signal may therefore be detectable over a long distance. In this case mixer  66  may weigh the GPS indications much higher than Bluetooth indications sent by computing devices  4 A and  4 B to proximity module  24 . 
     In another example, computing devices  4 A and  4 B may be an office building in Manhattan leading to different environment than the mountaintop of the previous example. In the current example, computing devices  4 A and  4 B may get receive a GPS signal at all, or only a few satellites may be visible. Computing devices  4 A and  4 B may determine the geopositions received from the satellites are characterized by a large margin of error with the location it returns. Even if a high margin of error is not detected, computing devices  4 A and  4 B may use data based on previous experiences. The data may indicate that signal reflections are more likely in a dense metropolitan area and therefore geopositions are characterized by higher margins of error. The office building may, however, be embedded in a rich radio frequency environment with many Bluetooth sources (e.g., included in other computing devices). The larger number of Bluetooth sources may therefore provide a higher confidence using Bluetooth indications to determine whether users  2 A and  2 B are within a physical presence of one another. 
     In some examples, mixer  66  may determine a probability of being in a particular class as p(ω|x), wherein ω can take either the value “within physical presence” or its complement “not within a physical presence.” The value x may be the entirety of the input available mixer  24 , for example, confidence values from GPS agent  60 , Bluetooth agent  62 , audio recognition agent  64  or any other agent associated with a modality that may be used to determine whether users associated with computing devices are within a physical presence of one another. 
     Given the set of agents M ( 60 - 64 , etc.) as shown in  FIG. 2  (which may be referred to as experts in some example techniques), mixer  66  may interrogate any individual agent m to learn what likelihood the agent assigns to the two users being within a physical presence of one another p(ω|x,m). In some examples, the individual agents may have access to the entirety of indications received from computing devices  4 A and  4 B. Agents  60 -, in general, may access data in the indications across modalities. In one example, if many indications are received in a vector from, for example, computing device  4 A, agents  60 - 64  may ignore one or more indications in the vector. For instance, GPS agent  60  may ignore all indications available to it except for the GPS indications and return a confidence value (e.g., probability) indicating whether users associated with computing devices are within a physical presence of one another by integrating over the area of uncertainty (e.g., margins of error) associated with the GPS indications. 
     The framework implemented by mixer  66  weights each agent  60 - 64  with a term supplied by a critic p(m|x), which indicates a probability that the agent corresponding to the critic is the correct agent to trust given a particular indication. In some examples, the critics may be associated with mixer  66  and/or a corresponding agent. The critics, like the agents, may have access to all of the indications from computing devices  4 A and  4 B but may choose not to use one or more of the available indications. If the critic anticipates that an agent is likely to return a spurious result then the critic may give very little weight to the confidence value generated by the agent, allowing other agents to drive the decision. For instance, GPS agent  60  may place a high probability of users  2 A and  2 B being within a physical presence of one another if both computing devices associated with users  2 A and  2 B, respectively, report the same location but with a large error, say ±100 meters. The critic would then notice the large error and discount the likelihood that the agent is generating useful data. Consequently, when mixer  66  determines whether users associated with computing devices are within a physical presence of one another based on confidence values received from agents  60 - 64 , confidence value associated with GPS agent  60  may receive less weight than confidence values from other agents. 
     The framework used by mixer  66  may also use an experience term. As one example, an experience term may discount a confidence value from GPS agent  60  if the reported location happens to be from an area where a high level of unexpected radio frequency noise has been observed in the past. For instance, GPS indications generated while in downtown Manhattan may be based on satellite signals that are reflected off tall buildings, leading GPS agent to determine less precise confidence values that even the critic cannot anticipate. Consequently, the confidence value may be weighted less by the experience term. An advantage of this framework is that it allows appropriate agents to provide greater include in decisions made by mixer  66  based on the experience term. 
     The framework implemented in mixer  66  may accommodate any number of modalities. In some examples, a modality may include a Passive Radio Frequency Spectrum. For instance, numerous techniques exist for turning a list of IEEE 802.11 signal strengths into a fingerprint suitable for proximity determination. Some may also be applied to Bluetooth signals. Such techniques could be used by the framework implemented in mixer  66 . If some techniques work well in one situation and not another then a critic and experience terms can prevent them from polluting the decision. A partial list of Wifi fingerprinting algorithms include: sum of differences of normalized signals, cosine similarity, and Spearman ranking. Such techniques may be implemented by an agent when receiving indications associated with a passive radio frequency spectrum. 
     As another example, a modality may include an Active Radio Frequency Spectrum. For instance, Bluetooth allows each handset to become a broadcaster as well as a listener. Bluetooth agent  62  may use the fact that computing device  4 A detection of computing device  4 B&#39;s device identifier as a measure of whether users  2 A and  2 B are within a physical presence of one another. 
     As described above in reference to  FIG. 1 , some location services, including GPS, provide both a location (e.g., geoposition) and an error bound (e.g., margin of error). That error bound may be taken as a parameter defining some distribution over location of the actual position of a computing device. That distribution might be uniform, or normal, or some other family. Computing the difference between these random variables yields a new distribution. Integrating over this distribution, bounded to the distances deemed to be “in close proximity” will yield the probability that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. 
       FIG. 3  is a block diagram illustrating further details of one example of a server device shown in  FIG. 1 , in accordance with one or more aspects of the present disclosure.  FIG. 3  illustrates only one particular example of server device  22 , and many other examples of server device  22  may be used in other instances. 
     As shown in the specific example of  FIG. 3 , server device  22  includes one or more processors  80 , a communication unit  84 , one or more storage devices  88 , input device  82 , and output device  86 . Server device  22 , in one example, further includes applications  92  and operating system  94  that are executable by server device  22 . Each of components  80 ,  82 ,  84 ,  86 , and  88  may be interconnected (physically, communicatively, and/or operatively) for inter-component communications. In some examples, communication channels  90  may include a system bus, network connection, interprocess communication data structure, or any other channel for communicating data. As one example in  FIG. 3 , components  80 ,  82 ,  84 ,  86 , and  88  may be coupled by one or more communication channels  90 . Applications  92  (includes modules  24 ,  26 ,  28 ,  30 , and  32 ) and operating system  94  may also communicate information with one another as well as with other components in server device  22 . 
     Processors  80 , in one example, are configured to implement functionality and/or process instructions for execution within server device  22 . For example, processors  80  may be capable of processing instructions stored in storage device  88 . 
     One or more storage devices  88  may be configured to store information within server device  22  during operation. Storage device  88 , in some examples, is described as a computer-readable storage medium. In some examples, storage device  88  is a temporary memory, meaning that a primary purpose of storage device  88  is not long-term storage. Storage device  88 , in some examples, is described as a volatile memory, meaning that storage device  46  does not maintain stored contents when the computer is turned off. Examples of volatile memories include random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories known in the art. In some examples, storage device  88  is used to store program instructions for execution by processors  80 . Storage device  88 , in one example, is used by software or applications running on server device  22  (e.g., applications  88 ) to temporarily store information during program execution. 
     Storage devices  88 , in some examples, also include one or more computer-readable storage media. Storage devices  88  may be configured to store larger amounts of information than volatile memory. Storage devices  88  may further be configured for long-term storage of information. In some examples, storage devices  88  include non-volatile storage elements. Examples of such non-volatile storage elements include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. 
     Server device  22 , in some examples, also includes one or more communication units  84 . Server device  22 , in one example, utilizes communication unit  84  to communicate with external devices via one or more networks, such as one or more wireless networks. Communication unit  84  may be a network interface card, such as an Ethernet card, an optical transceiver, a radio frequency transceiver, or any other type of device that can send and receive information. Other examples of such network interfaces may include Bluetooth, 3G and WiFi radios computing devices as well as USB. In some examples, server device  22  utilizes communication unit  84  to wirelessly communicate with an external device such as computing devices  4  of  FIG. 1 , or any other computing device. 
     Server device  22 , in one example, also includes one or more input devices  82 . Input device  82 , in some examples, is configured to receive input from a user through tactile, audio, or video feedback. Examples of input device  82  include a presence-sensitive screen, a mouse, a keyboard, a voice responsive system, video camera, microphone or any other type of device for detecting a command from a user. In some examples, a presence-sensitive screen includes a touch-sensitive screen. 
     One or more output devices  86  may also be included in server device  22 . Output device  86 , in some examples, is configured to provide output to a user using tactile, audio, or video stimuli. Output device  86 , in one example, includes a presence-sensitive screen, a sound card, a video graphics adapter card, or any other type of device for converting a signal into an appropriate form understandable to humans or machines. Additional examples of output device  86  include a speaker, a cathode ray tube (CRT) monitor, a liquid crystal display (LCD), or any other type of device that can generate intelligible output to a user. 
     Server device  22  may include operating system  94 . Operating system  94 , in some examples, controls the operation of components of server device  22 . For example, operating system  54 , in one example, facilitates the interaction of applications  92  with processors  80 , communication unit  84 , storage device  88 , input device  82 , and output device  86 . As shown in  FIG. 3 , applications  92  may include proximity module  24 , event module  26 , logging module  28 , visual module  30  and social networking module  32  as described in  FIG. 1 . Applications  92  may each include program instructions and/or data that are executable by server device  22 . As one example, proximity module  24  may include instructions that cause server device  22  to perform one or more of the operations and actions described in the present disclosure. 
     In accordance with aspects of the present disclosure, communication unit  84  may receive a first group of indications associated with a first group of modalities of computing device  4 A and a second group of indications associated with a second group of modalities of computing device  4 B. Proximity module  24  may use indications of the first and second groups of modalities to determine whether users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. 
     As shown in  FIG. 3 , proximity module  24  may determine a confidence value for at least one modality of the first or second groups of modalities based at least in part on an indication associated with the at least one modality. The confidence value determined by proximity module  24  may indicate a likelihood that a first user and a second user associated with first and second computing devices, respectively, are within a physical presence of one another. The one or more indications used to generate the confidence value may be included in at least the first or second group of indications. Proximity module  24  may determine that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another based at least in part on the confidence value for the at least one modality. Upon determining that the confidence value is greater than a boundary value, performing, one or more of proximity module  24 , event module  26 , logging module  28  and/or visualization module  30  may perform one or more operations to indicate that users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another. 
     In some example operations, proximity module  24  may send one or more messages to computing devices  4 A and/or  4 B that indicate that users  2 A and  2 B are within a physical presence of one another. In another example, event module  26  may determine an event associated with a location or area that includes at least one of computing devices  4 A or  4 B. Event module  26  may send one or more messages to computing devices  4 A and/or  4 B that indicate the event and enable users to share content about the event. In another example operation, logging module  28  may generate log data that indicates users  2 A and  2 B are within a physical presence of one another. Logging module  28  may, in another example, log data that indicates that users  2 A and  2 B are within a physical presence of one another. In still other example operations, visualization module  30  may format, arrange and/or perform other operations to modify the appearance of information sent by server device  22  to computing devices  4 A and/or  4 B. 
     In some examples, techniques of the present disclosure provide privacy and/or security functionality for any data collected or processed by server  22 . For instance, users may opt out of some or all functionality described in the present disclosure. In this way, users can choose whether techniques of the present disclosure are applied to data received from one or more devices. In some examples, techniques of the present disclosure provide symmetric and/or asymmetric control over user data. For instance, in one example, users  2 A and  2 B may provide selections to server device  22  indicating they wish to receive messages indicating when other users and computing devices are within a physical presence of them. Users  2 A and  2 B may also provide selections to server device  22  indicating that they wish to enable server device  22  to determine whether they are in the physical presence of one or more other users and/or computing devices and share such information with other computing devices. Such controls may similarly be applied to logging by logging module  28  such that all, some or no data about a user is logged according to user preferences specified by a user. Users may further control whether to be associated with events determined by server device  22 . 
     In some examples, techniques of the disclosure enable a user to set preferences to share only a limited amount of information associated with a user in a social networking service with other users. For instance, if proximity module  24  determines that users  2 A and  2 B are within a physical presence of one another, user preferences may specify that computing device  4 B only receive a subset of social networking data associated with user  2 A in a social networking service. In this way, users may control how their information is shared with other users. 
     Techniques of the present disclosure may also enable users to control access to content shared using event documents, social groups, group chats or any other components associated with users that are within a physical presence of one another. For example, users may provide preferences that specify which other users can view content on an event document. Users may further delete or modify content associated with such documents. In other examples, user may provide preferences to control which users have access to participating in a group chat created in response to server device  22  determining that users associated with computing devices are within a physical presence of one another. Generally, techniques of the disclosure enable a user to provide any number of preferences to control access of any information associated with a user. 
       FIG. 4  is an example of a computing device that is operable to display a graphical user interface, in accordance with one or more techniques of the present disclosure. As described in reference to  FIG. 1 , logging module  28  may log one or more events as data in logging data  36 . In other examples, when proximity module  24  determines that users are associated with computing devices are within a physical presence of one another, logging module  28  may log data in logging data  36  that indicates, for example, users  2 A and  2 B were within a physical presence of one another and/or that computing devices  4 A and  4 B were e within a predetermined distance. Logging data  36  may indicate associations between times, dates, users, locations, events, etc. For instance, logging module  36  may determine users  2 A and  2 B are attending an event based at least in part on one or more confidence values generated by proximity module  24  and further on geoposition and/or other information indicating the users are attending the event. Consequently, logging module  28  may log logging data that indicates users  2 A and  2 B are associated with the event. In this way, techniques of the present disclosure using logging module  28  and logging data  36  enable users to later determine who they have spent their time with, what they were doing, where they were doing it, and/or what events they attended. 
     In some examples, user  2 A may later wish to view logging data. As shown in  FIG. 4 , computing device  4 A may include communication module  6 A, input device  8 A, output device  10 A, short-range communication device  12 A, and GPS device  13 A as described in  FIG. 1 . User  2 A may provide a user input at input device  8 A that causes communication module  6 A to send a message to server device  22  to request log data associated with user  2 A. The message may include a user identifier that identifies user  2 A. In some examples, the message may further indicate one or more parameters to specify which logging data user  2 A is requesting. For instance, the message may specify the type of log data requested, the time range of the log data requested, the quantity of log data requested, or any other suitable parameter that can be used to select a set of log data. Upon receiving the message, logging module  28  may retrieve the log data based at least in part on the user identifier that identifies user  2 A. Logging module  28  may, in some examples, use the parameters included in the message to further refine the retrieval of the log data. Logging module  28  may then send a message to computing device  4 A for display at output device  10 A. 
     In some examples, visualization module  30  may format the log data for proper display at computing device  4 A. For instance, visualization module  30  may dynamically generate a Hypertext Transfer Protocol Language (HTML) document that includes the log data in a format presentable to user  2 A. In some examples, visualization module  30  may format the log data for improved display based at least in part on the capabilities of computing device  4 A (e.g., processing performance, display size and resolution, etc.). 
     Computing device  4 A upon receiving the logging data from server  22  may display logging data in GUI  100  using output device  10 A. Many various types of logging data may be included in GUI  100  by communication module  6 A and presented in multiple different configurations. For instance, GUI  100  may display a life log  110  that, for a given time range, displays a list of users that were nearby user  2 A. For instance, life log  110  may display event indicators  102 A,  102 B, and  102 C for the time range of Sep. 14, 2011 through Sep. 21, 2011. In another example, life log  110  may display each user associated with a computing device that was within a physical presence of user  4 A. User indicators  104 A,  104 B,  104 C may indicate users that are associated with the event. In some examples, if user  2 A provides a user input to select one of the user indicators, the selected user may be associated with user  2 A, e.g., in a social networking service. In various examples, communication module  6 A may modify the time range of life log  110  based at least in user input received by input device  8 A. In some examples, the visual appearance of the event may be based at least in part on characteristics of the event. For instance, events longer in duration may be displayed by wider event indicators. Events corresponding to a particular group may have a common appearance such as color, pattern, shape, etc. 
     In some examples, logging module  28  may determine a frequency with which user  2 A is within a physical presence of other users associated with remote computing devices. For instance, logging module  28  may log logging data that indicates each time user  2 A is within a physical presence of another user. Logging module  28  may, automatically or in response to receiving a request from computing device  4 A, determine the frequency with which user  2 A is within a physical presence of other users. In one example, upon receiving such data indicating the frequencies, communication module  6 A may case output device  10 A to display user interface object  106 A. User interface object  106 A may include statistical, descriptive or any other type of information that indicates the frequencies that user  2 A is within a physical presence of other users associated with various computing devices. In this way, user interface object  106 A may display and rank how often and/or how long user  2 A is within a physical presence of one or more other users. For instance, user interface object  106 A may include a graph and a visual identifier of each user other than user  2 A associated with the graph. User  2 A can then identify the frequency with which user  2 A is within a physical presence each of the other users. 
     In some examples, logging module  28  may determine patterns that indicate recurring occurrences in which users spend their time. Logging module  28  determines, for example, that users  2 A and  2 B regularly meet for coffee on Tuesdays at 9:00 AM. For instance, logging module  28  may periodically, continuously, or on an event-driven basis, apply one or more pattern recognition techniques to logging data. A patter recognition technique may, for example, determine that two users are within a physical presence of one another at a repeating interval in the same location. Many other suitable pattern techniques may also be implemented by logging module  28 . Upon determining a pattern, logging module  28  may generate an event associated with the pattern. For instance logging module  28  may generate an event with information including “Coffee @ 9:00 AM every Tuesday with User A and User B.” Logging module  23  may log the newly generated event in log data to indicate the event associated with the pattern. 
     Communication module  6 A, in response to receiving a message with log data indicating one or more recurring events, may cause output device  10 A to display indications of the one or more recurring events in user interface object  106 B. In some examples, each recurring event may be represented by a selectable user interface object within user interface object  106 B. Upon selecting an object associated with the event, communication module  6 A may cause output device to prompt user  2 A to confirm the existence of the event associated with the object. In this way, communication module  6 A may display one or more events determined by server  22  and confirm whether user  2 A is associated with such recurring events. In some examples, a user interface object of an event may further include characteristics of the event such as title, date, time, location, users participating in the event, etc. 
     In some examples, log data received by communication module  6 A from server  22  may be displayed in user interface object  106 C to show user  2 A who they&#39;ve spend their time with and where they&#39;ve spent their time. As shown in  FIG. 4 , if user  2 A was within a physical presence of another user, the date and time, and location or event may be displayed by communication module  6 A. User  2 A may use the information displayed in user interface object  106 C to determine when and where they&#39;ve spend their time with other users. In some examples, user  2 A may search the log data using any number of criteria such as, date, time, location, users, etc. 
       FIG. 5  is an example of a computing device displaying a graphical user interface, in accordance with one or more techniques of the present disclosure. In some examples, if event module  26  determines the occurrence of an event, event module  26  may generate an event document  146  associated with the event. Event document  146  may be an HTML document or any other suitable file to associate content with an event. Content may include any visually or audibly displayable information (e.g., videos, audio recordings, text, etc.). As shown in  FIG. 5 , content may include event details  132 , calendar invitation control  134 , participant details  136 , map  138 , photos  140 , user images  142 A and  142 B, and text  144 A and  144 B associated with user images  142 A and  142 B. 
     In an example where users  2 A and  2 B are attending the same event, event module  26  may send one or more messages to computing devices  4 A and  4 B that indicate the event document for the event. For instance, the message may include a Uniform Resource Locator (URL) that is usable by computing devices  4 A and  4 B to access the event document. The message may further enable communication module  6 A to send messages to server  22  that associate content with the event page. 
     As shown in  FIG. 5 , computing device  4 A may include communication module  6 A, input device  8 A, output device  10 A, short-range wireless communication device  12 A, and GPS device  13 A as previously described in  FIG. 1 . In some examples, users associated with a common event may share content with each other using event document  146 . For instance, event document  146  may be modified and/or managed by a social networking service provided by social networking module  32 . Consequently, when users of the social networking service, e.g., user  2 A, that are associated with the common event send content to server  22 , social networking module  32  may associate the content with the event data representing the common event. For instance, user  2 A may provide a user input that causes communication module  6 A to generate an image using input device  8 A (e.g., a camera). Communication module  6 A may determine user  2 A has provided an input to associate the image with event document  146 . Consequently, communication module  6 A may send a message that indicates the event document to server device  22 . Communication module  6 A may further send an indication of content (e.g., an image or link to the image) to server  22  to be associated with event document  146 . 
     Social networking module  32  may receive the indication of content and associate the indication of the content with event document  146 . Consequently, social networking module  32  may associate the indication of content with event document  146 . In the example of  FIG. 4 , the image may be displayed as a photo in photos  140 . As shown in  FIG. 4 , event document  146  may include event details  132  that describe an event. Event details may include an event name, start time, end time, location, etc. Event document  146  may further include a calendar invitation control  134 . Calendar invitation control  134  may, when selected, enable a user to send calendar invitations to invite other users to the event associated with event document  146 . Event document  146  may also include participant details  136 . Participant details  136  may include a list of all users associated with the event. In some examples, each user may be represented by a user interface object. In response to determining a user interface object has been selected, social networking module  32  may send user provide information associated with the user of the selected object to computing device  4 A for display by output device  10 A. 
     Event document  146  may also include a map  138  that indicates a location of the event associated with event document  146 . For instance, the map may include a visual marker or other indicator that indicates geographically where the event is or has occurred. Event document may also include photos  140 . Photos  140  may be any images or videos send by a computing device associated with a user to server  22  to be associated with event document  146 . In some examples, event document  146  may include text  144 A,  144 B that is provided by users via computing devices. For instance, if a user attends an event and is further associated with an event, a status update may be displayed as text  144 A indicating that the user is now associated with the event. An image  142 A associated with the user in a social networking service may be displayed with text  144 A. In other examples, users may comment or otherwise submit information to event document  146  that is displayed, for example, as text  144 B. Similarly, an image  142 B associated with the user may be displayed with text  144 B 
     As shown in  FIG. 5 , event document  146  enables multiple users attending a common event to submit content that may be shared with other users attending the event. In some examples, all or portions of event document  146  may be generated, modified and stored at, e.g., server device  22  of  FIG. 1 . A computing device, e.g., a smartphone, may retrieve event document  146  from server device  22  and/or store event document  146  locally to display the contents of event document  146 . Event document  146  may include one or more input components that enable a user to modify content of event document  146 . The mobile computing device, upon receiving user input, may send data corresponding to the user input to, e.g., server device  22 . Sever  22  may modify content associated with event document  146  based on the data. Consequently, multiple different computing devices, upon receiving the updated event document, may see updates. Event document  146  may include any combination of content shown in  FIG. 5  or other content not described in  FIG. 5 . Moreover, in some examples, visualization module  30  may format event document  146  in any number of ways to change the layout and appearance of the document. 
       FIG. 6  is a flow diagram illustrating example operations of a computing device to determine whether users associated with computing devices are within a physical presence of one another, in accordance with one or more aspects of this disclosure. For purposes of illustration only, the example operations are described below within the context of remote server device  22  and computing devices  4 A and  4 B as shown in  FIG. 1 . 
     As shown in  FIG. 1 , server device  22  may receive a first group of indications associated with a first group of modalities from computing device  4 A ( 180 ). Server device  22  may also receive a second group of indications associated with a second group of modalities from computing device  4 B ( 180 ). In some examples, the modalities may be usable to determine whether users associated with computing devices are within a physical presence of one another. 
     Server device  22 , upon receiving the indications may determine a confidence value for at least one modality associated with the indications ( 184 ). The confidence value may indicate a likelihood that users  2 A and  2 B are within a physical presence of one another. As one example, server device  22  may determine a confidence value for a GPS modality. Server device  22  may generate the confidence value based on indications from computing device  4 A, indications from computing device  4 B or any combination thereof. In some examples, server device  22  may generate a plurality of confidence values for one or more modalities. 
     Server device  22  may determine whether users  2 A and  2 B are within a physical presence of one another ( 188 ). For instance, server device  22  may determine whether the confidence value is greater than a boundary value. If the confidence value is greater than the boundary value, server device  22  may determine that users  2 A and  2 B are within a physical presence of one another. If users  2 A and  2 B are not within a physical presence of one another, server device  22  may receive subsequent indications associated with modalities and make further determinations of whether users are associated with computing devices are within a physical presence of one another ( 202 ). If users  2 A and  2 B are within a physical presence of one another, logging module  28  may generate log data that indicates users  2 A and  2 B associated with computing devices  4 A and  4 B are within a physical presence of one another ( 204 ). In some examples, logging module  28  may generate log data that indicates computing devices  4 A and  4 B are within a predetermined distance. 
     In some examples, event module  26  may determine whether an event is associated with a location of computing devices  4 A and  4 B when users  2 A and  2 B are within a physical presence of one another ( 206 ). If the users  2 A and  2 B are within a physical presence of one another, event module  26  may associate users  2 A and  2 B with an event document ( 212 ). For instance, user identifiers that identify users  2 A and  2 B in a social networking service may be associated with the event document thereby enabling users  2 A and  2 B to easily share content about the event. In other examples, if an event is not associated with a location of computing devices  4 A and  4 B when users  2 A and  2 B are within a physical presence of one another, server device  22  may continue receiving indications from computing devices and determining if such computing devices are within a predetermined distance of one another ( 210 ). 
       FIG. 7  is a flow diagram illustrating example operations of a computing device to determine whether two or more computers are within a predetermined distance of one another, in accordance with one or more aspects of this disclosure. For purposes of illustration only, the example operations are described below within the context of server device  22  and computing devices  4 A and  4 B as shown in  FIG. 1 . 
     As shown in  FIG. 7 , server device  22  may receive a first group of indications from computing device  4 A that is associated with a first group of modalities ( 230 ). Server device  22  may also receive a second group of indications from computing device  4 B that is associated with a second group of modalities ( 230 ). The groups of modalities may be usable to determine whether users  2 A and  2 B are within a physical presence of one another. 
     Server device  22 , in some examples, may determine a confidence value for at least one modality of the first or second groups of modalities based at least in part on an indication associated with the at least one modality ( 230 ). In some examples, the confidence value may indicate a likelihood that users  2 A and  2 B are within a physical presence of one another. Server device  22  may further determine that users  2 A and  2 B are within a physical presence of one another, for example, by determining that the confidence value is greater than a boundary value. Upon determining that users  2 A and  2 B are within a physical presence of one another, server device  22  may perform an operation to indicate that the computing devices are within the predetermined distance ( 234 ). 
     In one example, the at least one modality is selected from a group consisting of a geoposition modality, an audio fingerprinting modality, a calendar data modality, and a short-range wireless communication modality. In another example, method includes determining, by the at least one computing device, a temporal identifier associated with an indication received from at least the first or second remote computing device, wherein the temporal identifier comprises at least one of a current date and time of the first or second computing device; and determining, by the at least one computing device, at least one event based at least in part on the temporal identifier. 
     In one example, the method includes receiving, by the at least one computing device, geoposition information associated with an indication received from at least the first or second remote computing device; and determining, by the at least one computing device, the at least one event based on the geoposition information. In another example, the method includes determining, by the at least one computing device, whether the at least one event is indicated in at least one event data source based on at least one of the temporal identifier and the geoposition information; and when the at least one event is indicated in at least one event data source, sending, by the at least one computing device, a message comprising information for display at the first remote computing device that indicates the event. In another example, the at least one event data source is selected from a group consisting of a document, calendar system, web page, email, instant message, and text message. 
     In one example, the method includes determining, by the at least one computing device, whether an event is indicated in at least one event data source based at least in part on one of the temporal identifier or the geoposition; and when the at least one event is not indicated in at least one event data source, determining, by the at least one computing device, whether to generate data indicating an event based on one or more event criteria; when at least one of the one or more event criteria is satisfied, generating, by the at least one computing device, the data indicating the event; and sending, by the at least one computing device, a message comprising information for display at the first remote computing device that indicates the event. 
     In another example, the one or more event criteria include: a distance between the first and second remote computing devices; a first frequency that the first and second remote computing devices are within the predetermined distance from one another; a second frequency that the first and second remote computing devices are within the predetermined distance from a geographic location; a third frequency that the first and second remote computing devices are within a predetermined distance at an indicated time; a density within a predetermined area of remote computing devices with at least the first or the second remote computing device; a first group of one or more relationships in a social networking service between a first user associated with the first remote computing device and one or more users associated with the one or more remote computing devices; and a second group of one or more relationships in the social network service between a second user associated with the second remote computing device and the one or more users associated with the one or more remote computing devices. 
     In one example, a method includes receiving, by the at least one computing device, one or more characteristics that describe the event; and associating, by the at least one computing device, the one or more characteristics with the event. In another example, the method includes in response to determining the at least one event, generating, by the at least one computing device, a social group in a social networking service associated with the event; sending, by the at least one computing device, a request to the first remote computing device to associate a first user with the social group in the social networking service, wherein the first user is associated with the first remote computing device; and in response to receiving a message to associate the first user with the social group, associating, by the at least one computing device, the first user with the social group in the social networking service. 
     In another example, the method includes in response to determining the at least one event, generating, by the at least one computing device, an event document associated with the event, wherein the event document comprises indications of content associated with the event; sending, by the at least one computing device, a message that indicates the event document to the first remote computing device; receiving, by the at least one computing device, an indication of content to associate with the event document; and in response to receiving the indication, associating, by the at least one computing device, the indicated content with the event document. 
     In one example, the method includes determining, by the at least one computing device, whether a relationship exists in a social networking service between a third user of the third remote computing device and at least one of a first user of the first remote computing device or a second user of the second remote computing device, wherein the third remote computing device is within the predetermined distance of at least one of the first or second remote computing devices; and when the relationship exists in the social networking service, sending, by the at least one computing device, a message comprising information for display at the third remote computing device that indicates the event. 
     In another example, the method includes determining, by the at least one computing device, a first user is associated with the first remote computing device and a second user is associated with the second remote computing device; and sending, by the at least one computing device, a message comprising information for display at the first remote computing device that indicates the first user associated with the first remote computing device is within the physical presence of the second user associated with the second remote computing device. In one example, the method includes determining, by the at least one computing device, a degree of similarity between at least one first audio fingerprint of the first remote computing device and at least one second audio fingerprint received from the second remote computing device, wherein the degree of similarity is within a range of degrees of similarity. 
     In another example, the method includes determining, by the at least one computing device, a margin of error associated with a geoposition of the first remote computing device and a margin of error associated with a geoposition of the second remote computing device. In one example, the method includes in response to determining that the first remote computing device and a third remote computing device are within the predetermined distance, determining, by the at least one computing device, whether a relationship exists in a social networking service between a third user of the third remote computing device and a second user of the second remote computing device; and when the relationship exists between the second and third users, sending, by the at least one computing device, a message to the first computing device to indicate a potential relationship between the first user and the third user. 
     In one example, the method includes determining, by the at least one computing device, a plurality of confidence values for a plurality of modalities of the first or second groups of modalities, wherein the plurality of confidence values indicate a likelihood that the plurality of modalities indicate whether the first user associated with the first remote computing device is within the physical presence of the second user associated with the second remote computing device. In another example, the method may include storing, by the at least one computing device, log data that indicates the first user associated with the first remote computing device is within the physical presence of the second user associated with the second remote computing device. In one example, the method may include determining, by the at least one computing device, an event attended by at least one of the first user or the second user; and storing, by the at least one computing device, second log data to associated the event with the first log data. 
     In another example, the method may include receiving, by the at least one computing device, a first message from the first remote computing device to request log data associated with the user, wherein the message comprises a user identifier that identifies the user; retrieving, by the at least one computing device, log data based at least in part on the user identifier; and sending, by the computing device, a second message comprising the log data for display at the first remote computing device. In one example, the method may include determining, by the at least one computing device, that the first user associated with the first remote computing device is within the physical presence of the second user associated with the second remote computing device in accordance with a pattern that indicates a recurring occurrence; generating, by the at least one computing device, an event associated with the pattern; and storing, by the at least one computing device, log data that indicates the event associated with the pattern. In another example, the method may include querying, by the at least one computing device, log data associated with the first user, wherein the log data indicates a plurality of frequencies indicating occurrences when the first user is within a physical presence of users associated with a plurality of remote computing devices. 
     The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A control unit including hardware may also perform one or more of the techniques of this disclosure. 
     Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components. 
     The techniques described in this disclosure may also be embodied or encoded in an article of manufacture including a computer-readable storage medium encoded with instructions. Instructions embedded or encoded in an article of manufacture including a computer-readable storage medium encoded, may cause one or more programmable processors, or other processors, to implement one or more of the techniques described herein, such as when instructions included or encoded in the computer-readable storage medium are executed by the one or more processors. Computer readable storage media may include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a compact disc ROM (CD-ROM), a floppy disk, a cassette, magnetic media, optical media, or other computer readable media. In some examples, an article of manufacture may include one or more computer-readable storage media. 
     In some examples, a computer-readable storage medium may include a non-transitory medium. The term “non-transitory” may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in RAM or cache). 
     Various embodiments have been described. These and other embodiments are within the scope of the following claims.