Patent Publication Number: US-2012041825-A1

Title: Contextual translation of non-interactive advertisements into interactive advertisements

Description:
BACKGROUND 
     The present disclosure relates to an interactive operating environment, and more particularly, to providing improved apparatus and methods of generating interactive advertisements to users of a device based upon exposure and context of experiencing non-interactive advertisements. 
     For many years, companies have tried to brand their products, satisfy existing consumers, and reach potential new consumers through traditional means. The evolution includes advertising ranging from print forms like newspapers, magazines, brochures, newsletters, press releases, and billboards, to event-related activities, like sponsorships, seminars, point-of-sale and promotional programs, to broadcast media, like radio, television, cable, and recently satellite cable. 
     In recent years, there has been a rise of advertising that is more targeted and tailored to individual consumers, with new forms of previously so-called direct advertising. New endeavors have sought to interact directly with consumers through pull campaigns and push campaigns, and make advertising more measurable to bring advertisers specific consumer data mining information bearing on consumer buying habits, trends and predicted future habits. Advances in technology outlets combined with marketing ingenuity have expanded the old direct mail marketing campaigns into new branches, including telemarketing, point-of-sale campaigns, computer platforms, and most recently distribution and measurement through telecommunications networks. 
     With respect to the latter, perhaps the greatest platform for the new world of marketing has been the same as the greatest platform for information exchange in the last decade, namely the Internet. Through such avenues as branded websites, banner ads, pop-up ads, targeted e-mails, portal sponsorships, to name a few examples, advertisers have been able to hone in on target audiences. Through defined metrics and innovative semantics, like served impressions, click-through rate (CTR), cost per action (CPA), cost per click (CPC), cost per sale (CPS), and cost per thousand (CPM), to name a few, advertisers have been able to measure the results of targeted ads and objectively set fees based on performance results. Along with these new advances, and because of the increasingly cosmopolitan nature of business, geopolitics, and integrated telecommunications networks, so too has advertising become increasingly global in nature. 
     Traditional static advertising venues such as billboards have received some improvements by incorporating active, electronic elements for dynamically changing advertisements. Thereby, the media content is more interesting and can be varied in order to better tailor the advertisements for a targeted audience. For example, those commuting downtown for work can constitute a different audience demographic as compared to midday drivers. While such added dynamism has increased the advertising value of traditional advertising venues, these dynamic advertising venues still lack the degree of targeting and marketing feedback that are enjoyed by more interactive advertising channels. 
     In particular, as non-interactive media, it is difficult to ascertain interest by potential customers who may have passively viewed or listened to advertisements (e.g., television, billboards, etc.). 
     SUMMARY 
     The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later. 
     In one aspect, a method of delivering advertisements is provided. The method includes determining exposure to a non-interactive advertisement. The method further includes determining at least one behavioral context parameter corresponding to the exposure to the non-interactive advertisement. The at least one behavioral context parameter includes an exposure duration of the exposure to the non-interactive advertisement. The method further includes determining whether a correlation exists between the non-interactive advertisement and the at least one behavioral context parameter. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. Additionally, the method includes generating a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists. 
     In another aspect, at least one processor is provided for delivering advertisements. A first module determines exposure to a non-interactive advertisement. A second module determines at least one behavioral context parameter corresponding to the exposure to the non-interactive advertisement. The at least one behavioral context parameter includes an exposure duration of the exposure to the non-interactive advertisement. A third module determines whether a correlation exists between the non-interactive advertisement and the at least one behavioral context parameter. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. A fourth module generates a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists. 
     In an additional aspect, a computer program product including a computer-readable storage medium is provided for delivering advertisements. The computer-readable storage medium includes at least one instruction for causing a computer to determine exposure to a non-interactive advertisement. The computer-readable storage medium further includes at least one instruction for causing the computer to determine at least one behavioral context parameter corresponding to the exposure to the non-interactive advertisement. The at least one behavioral context parameter includes an exposure duration of the exposure to the non-interactive advertisement. The computer-readable storage medium further includes at least one instruction for causing the computer to determine whether a correlation exists between the non-interactive advertisement and the at least one behavioral context parameter. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. The computer-readable storage medium further includes at least one instruction for causing the computer to generate a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists. 
     In a further aspect, an apparatus is provided for delivering advertisements. The apparatus includes means for determining exposure to a non-interactive advertisement. The apparatus further includes means for determining at least one behavioral context parameter corresponding to the exposure to the non-interactive advertisement. The at least one behavioral context parameter includes an exposure duration of the exposure to the non-interactive advertisement. Further, the apparatus includes means for determining whether a correlation exists between the non-interactive advertisement and the at least one behavioral context parameter. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. Additionally, the apparatus includes means for generating a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists. 
     In yet another aspect, an apparatus is provided for delivering advertisements. The apparatus includes an exposure determiner, a behavioral context determiner, a correlator, and a network interface. The exposure determiner determines exposure to a non-interactive advertisement. The behavioral context determiner determines at least one behavioral context parameter corresponding to the exposure to the non-interactive advertisement. The at least one behavioral context parameter includes an exposure duration of the exposure to the non-interactive advertisement. The correlator determines whether a correlation exists between the non-interactive advertisement and the at least one behavioral context parameter. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. The correlator further generates a trigger. The network interface obtains an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists based upon the trigger. 
     To the accomplishment of the foregoing and related ends, the one or more aspects comprise the features hereinafter described in detail and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative features of the one or more aspects. These features are indicative, however, of but a few of the various ways in which the principles of various aspects may be employed, and this description is intended to include all such aspects and their equivalents. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The disclosed aspects will hereinafter be described in conjunction with the appended drawings, provided to illustrate and not to limit the disclosed aspects. 
         FIG. 1  illustrates a schematic diagram of an apparatus for delivery of advertisements, according to one aspect. 
         FIG. 2  illustrates a flow diagram for a methodology or sequence of operations for delivery of interactive advertisements, according to one aspect. 
         FIG. 3  illustrates a schematic diagram of a distributed system of a server and a client that performs delivery of interactive advertisements, according to one aspect. 
         FIG. 4  illustrates a flow diagram of an exemplary methodology for targeted delivery of interactive advertisements, according to one aspect. 
         FIG. 5  illustrates a schematic diagram of one or more aspects of determining sufficient exposure and applicable heuristic triggers associated with an audio or video type of non-interactive advertisement, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 6  illustrates a schematic diagram of one or more aspects of determining sufficient exposure and applicable heuristic triggers associated with a static type of non-interactive advertisement, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 7  illustrates a schematic diagram of one or more aspects of determining user context relative to others to validate or discount exposure and heuristic triggers, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 8  illustrates a schematic diagram of one or more aspects of determining user based on device usage to validate or discount exposure and heuristic triggers, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 9  illustrates a schematic diagram of one or more aspects of determining user context based on history or a time window to validate or discount exposure and heuristic triggers, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 10  illustrates a schematic diagram of one or more aspects of sending an interactive advertisement corresponding to a non-interactive advertisement to a user, according to one aspect of the methodology of  FIG. 4 . 
         FIG. 11  illustrates a schematic diagram for a system such as a mobile device having logical grouping of electrical components for delivery of advertisements, according to one aspect. 
         FIG. 12  illustrates a schematic diagram of an exemplary computing environment, such as for a network server, remote to a mobile device, according to one aspect. 
         FIG. 13  illustrates a schematic diagram of an exemplary computing environment, such as a mobile device, for communicating with a remote network server, according to one aspect. 
         FIG. 14  illustrates a schematic diagram of a distributed architecture for detecting exposure to a non-interactive advertisement and for receiving a corresponding interactive advertisement when appropriate exposure and behavioral context are determined, according to one aspect. 
     
    
    
     DETAILED DESCRIPTION 
     When a user walks in a busy shopping mall or in the middle of Times Square in New York, the user is exposed to physical advertisements for products or services. The described apparatus and methods enable translation of those physical advertisements into interactive advertisements to entice the user to learn more about, or purchase, the advertised product or service. In one aspect, the interactive advertisement may entice the user to enter a nearby physical store or to try the advertised product or service. In another aspect, when a user watches a particular channel on TV, there is an opportunity to translate a non-interactive TV advertisement being watched by the user into an interactive advertisement. In this disclosure, behavioral context information is used to determine a user&#39;s interest in a non-interactive advertisement, and to trigger obtaining a translation of the non-interactive advertisement into an interactive advertisement. 
     As used herein, an advertisement is broadly defined as encompassing a communication, promotion, campaign, etc., with an intent to illicit consumer interest in a particular good or service or to enhance brand identification. Although visual advertisements are depicted in an exemplary manner, it should be appreciated that advertisements can utilize one or more sensory modes (e.g., tactile including Braille lettering, scent, graphical imagery, text, audio including spoken words and music, etc.). 
     As used herein, a non-interactive advertisement is any advertisement that does not allow for user feedback. For example, a non-interactive advertisement includes, but is not limited to, an audio advertisement that can be heard or a physical advertisement that can be seen, such as in a store, walking down a street, in a mall, etc. Using behavioral context information, including but not limited to a user&#39;s actions relative to the non-interactive advertisement, a user&#39;s actions relative to others, a difference between a user&#39;s and others&#39; actions relative to the non-interactive advertisement, advertisement location, user&#39;s location, TV channel and the user&#39;s wireless network, and one or more context-related thresholds, the apparatus and methods described herein trigger obtaining a monetizable, interactive, wireless, on-the-go advertisement corresponding to the non-interactive advertisement. 
     In one aspect, the described apparatus and methods utilize the behavioral context information to define one or more dimensions of user context, which can be utilized to determine an interest level in a non-interactive advertisement. For example, in one dimension, the behavioral context information quantifies a user context relative to others. In other words, this dimension determines what the user is doing as compared to what others are doing. Further, for example, in another dimension, the behavioral context information quantifies a user context relative to the user himself In other words, this dimension determines how a certain current context parameter relates to other current context parameters that define a current user context. Moreover, for example, in yet another dimension, the behavioral context information quantifies a user context relative to a user history. In other words, this dimension determines how a current user context, or a current user context parameter, compares to prior user contexts or context parameters, in order to determine whether a pattern exists, or to otherwise explain the user behavior. Thus, each dimension may be used, individually or in combination with one or more of the other dimensions, in order to determine if the behavioral context information indicates that a user is interested in the non-interactive advertisement, thereby triggering acquisition of a corresponding interactive advertisement. 
     Various aspects of the disclosure are further described below. It should be apparent that the teaching herein can be embodied in a wide variety of forms and that any specific structure or function disclosed herein is merely representative. Based on the teachings herein one skilled in the art should appreciate that an aspect disclosed herein can be implemented independently of other aspects and that two or more of these aspects can be combined in various ways. For example, an apparatus can be implemented or a method practiced using any number of the aspects set forth herein. In addition, an apparatus can be implemented or a method practiced using other structure or functionality in addition to or other than one or more of the aspects set forth herein. As an example, many of the methods, devices, systems, and apparatus described herein are described in the context of providing dynamic queries and recommendations in a mobile communication environment. One skilled in the art should appreciate that similar techniques could apply to other communication and non-communication environments as well. 
     As used in this disclosure, the term “content” and “objects” are used to describe any type of application, multimedia file, image file, executable, program, web page, script, document, presentation, message, data, meta-data, or any other type of media or information that may be rendered, processed, or executed on a device. 
     As used in this disclosure, the terms “component,” “system,” “module,” and the like are intended to refer to a computer-related entity, either hardware, software, software in execution, firmware, middle ware, microcode, or any combination thereof. For example, a component can be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, or a computer. One or more components can reside within a process or thread of execution and a component can be localized on one computer or distributed between two or more computers. Further, these components can execute from various computer readable media having various data structures stored thereon. The components can communicate by way of local or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, or across a network such as the Internet with other systems by way of the signal). Additionally, components of systems described herein can be rearranged or complemented by additional components in order to facilitate achieving the various aspects, goals, advantages, etc., described with regard thereto, and are not limited to the precise configurations set forth in a given figure, as will be appreciated by one skilled in the art. 
     Additionally, the various illustrative logics, logical blocks, modules, and circuits described in connection with the aspects disclosed herein can be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any suitable combination thereof designed to perform the functions described herein. A general-purpose processor can be a microprocessor, but, in the alternative, the processor can be any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other suitable configuration. Additionally, at least one processor can comprise one or more modules operable to perform one or more of the operations or actions described herein. 
     Moreover, various aspects or features described herein can be implemented as a method, apparatus, or article of manufacture using standard programming or engineering techniques. Further, the operations or actions of a method or algorithm described in connection with the aspects disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. Additionally, in some aspects, the operations or actions of a method or algorithm can reside as at least one or any combination or set of codes or instructions on a machine-readable medium or computer readable medium, which can be incorporated into a computer program product. Further, the term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media. For example, computer-readable media can include but are not limited to magnetic storage devices (e.g., hard disk, floppy disk, magnetic strips, etc.), optical disks (e.g., compact disk (CD), digital versatile disk (DVD), etc.), smart cards, and flash memory devices (e.g., card, stick, key drive, etc.). Additionally, various storage media described herein can represent one or more devices or other machine-readable media for storing information. The term “computer-readable medium” can include, without being limited to, wireless channels and various other media capable of storing, containing, or carrying instruction, or data. Non-transitory computer-readable medium can include tangible medium that retain computer data structures, instructions and code for an extended period of time. 
     Furthermore, various aspects are described herein in connection with a mobile device. A mobile device can also be called a system, a subscriber unit, a subscriber station, mobile station, mobile, mobile device, cellular device, multi-mode device, remote station, remote terminal, access terminal, user terminal, user agent, a user device, or user equipment, or the like. A subscriber station can be a cellular telephone, a cordless telephone, a Session Initiation Protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device having wireless connection capability, or other processing device connected to a wireless modem or similar mechanism facilitating wireless communication with a processing device. 
     In addition to the foregoing, the word “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the word exemplary is intended to present concepts in a concrete fashion. Furthermore, as used in this application and the appended claims, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, in this example, X could employ A, or X could employ B, or X could employ both A and B, and thus the statement “X employs A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. 
     As used herein, the terms to “infer” or “inference” refer generally to the process of reasoning about or deducing states of a system, environment, or user from a set of observations as captured via events or data. Inference can be employed to identify a specific context or action, or can generate a probability distribution over states, for example. The inference can be probabilistic—that is, the computation of a probability distribution over states of interest based on a consideration of data and events. Inference can also refer to techniques employed for composing higher-level events from a set of events or data. Such inference results in the construction of new events or actions from a set of observed events or stored event data, whether the events are correlated in close temporal proximity, and whether the events and data come from one or several event and data sources. 
     Various aspects are now described with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more aspects. It may be evident, however, that the various aspects may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing these aspects. 
     With initial reference to  FIG. 1 , a system  99  for enabling obtaining of interactive advertisements includes an apparatus  100  having an exposure determiner  101  that determines exposure  104  of a user  106  to a non-interactive advertisement  108 . For example, a transceiver  102  can assist in determining this exposure  104  based upon remotely sensed information relayed to the apparatus  100 . Alternatively, or in addition, the exposure  104  can in part be determined by directly detecting the presence of the non-interactive advertisement  108  (e.g., detecting an electromagnetic signal emanating from the non-interactive advertisement  108 ). As another alternative, or another addition, the exposure  104  can be based in part upon receiving a signal conveying location information (e.g., position/location system signal, direction finding based on fixed broadcast sources, etc.). The apparatus  100  may further include a computing platform  110  having a behavioral context determiner  111  that determines one or more behavioral context parameters  112  corresponding to the exposure  104  to the non-interactive advertisement  108 , wherein the one or more behavioral context parameters  112  include an exposure duration  114  of the exposure  104  to the non-interactive advertisement  108 . The computing platform  110  further has a correlator  113  that determines whether a correlation  115  exists between the non-interactive advertisement  108  and the one or more behavioral context parameters  112 , wherein the correlation  115  includes, at least in part, determining that the exposure duration  114  achieves an exposure threshold  116 . The correlator  113  generates a trigger  118  that obtains an interactive advertisement  120  corresponding to the non-interactive advertisement  108  if the correlation  115  exists, such as via network interface  122 . 
     In one aspect, the apparatus  100  comprises a handset that is entirely or largely able to autonomously obtain interactive advertisements  120  as well as the requisite one or more behavioral context parameters  112  and to determine exposure duration  114 . In another aspect, interactive advertisements  120  are pushed to the apparatus  100  with entirely or a substantial portion of the processing performed remotely. In another aspect, the apparatus  100  is a distributed computing platform wherein a certain functions are performed remotely or collaboratively performed both locally and remotely. 
     For clarity, exemplary aspects are described herein with regard to mobile devices. However, it should be appreciated that with the benefit of the present disclosure, certain implementations can utilize fixed, distributed, or portable systems or devices. For instance, a facility or pedestrian area can have one or more interactive kiosks, workstations, or devices that can perform portions of the disclosed aspects. For instance, one device can sense exposure duration while another device serves to present an interactive advertisement to a user. 
     In  FIG. 2 , a methodology or sequence of operations  200  is provided for obtaining interactive advertisements, according to one aspect. Determining exposure to a non-interactive advertisement is performed at  204 . At  206 , one or more behavioral context parameters corresponding to the exposure to the non-interactive advertisement are determined The one or more behavioral context parameters include, for example, an exposure duration of the exposure to the non-interactive advertisement. 
     The methodology or sequence of operations  200  further includes determining whether a correlation exists between the non-interactive advertisement and the one or more behavioral context parameters at  208 . The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. In an aspect, for example, determining that the exposure duration achieves the exposure threshold may comprise determining that the exposure duration is greater than a sample population exposure time that is a function of a plurality of user exposure times corresponding to the non-interactive advertisement collected from a plurality of users. Further, for example, the sample population exposure time may include an average exposure time spent by the plurality of users in a vicinity of the non-interactive advertisement within a time period. The plurality of users may include either all the users in the vicinity of the non-interactive advertisement within the time period, or a subset of all the users in the vicinity of the non-interactive advertisement within the time period. In other aspects, determining that the exposure duration achieves the exposure threshold may include one or more of: determining that the exposure duration is greater than an average time the user spent at other locations within a time period; determining that the exposure duration is greater than a minimum exposure time; determining, in combination with the exposure duration and based on history information of user movements over a time period, that a pattern of historical exposure durations corresponds to the non-interactive advertisement; determining that the exposure duration does not occur during a time period corresponding to a user interaction with a wireless device; determining that the exposure duration is greater than a minimum portion of an advertisement duration, and determining that other advertisement exposure information for other advertisements adjacent in time to the non-interactive advertisement indicates a lack of other advertisement exposure; or determining that the exposure duration combined with a user behavior advertisement history indicates interest in the non-interactive advertisement. The user behavior advertisement history can include at least one of information indicating that the non-interactive advertisement is viewed more than once for greater than a minimum viewing time over a time period, information indicating that the non-interactive advertisement is viewed more than once across multiple channels over a time period, information indicating that the non-interactive advertisement is paused, rewound or replayed, or information indicating that a user rating greater than a minimum rating threshold is received during the exposure duration. 
     Also, the methodology or sequence of operations  200  further includes generating a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement, if the correlation exists at  210 . In an aspect, the interactive advertisement is obtained at a location determined based on one or more behavioral context parameters of the user. In other aspect, the interactive advertisement may be obtained by: receiving on a wireless device when location information of the wireless device corresponds to a vicinity of the non-interactive advertisement during the exposure duration; receiving at an e-mail account or on a wired communication device when the one or more behavioral context parameters identify a subject matter of the interactive advertisement as corresponding to historical purchases over the Internet using the wired communication device; receiving at an e-mail account or on a wired communication device when the one or more behavioral context parameters identify a user velocity greater than a velocity threshold; receiving via a text message; or receiving via an Internet Protocol television pop-up menu. 
     With reference to  FIG. 3 , the described aspects may be implemented in a system  300  for obtaining interactive advertisements  302 , according to one aspect. More particularly, the system  300  includes a communication device  304 , such as a mobile phone, Personal Digital Assistant (PDA), or a television that includes an exposure determiner  306  that is able to determine exposure to a non-interactive advertisement  308 . It should be noted that communication device  304  and non-interactive advertisement  308  may be the same as, or similar to, the respective apparatus  100  and non-interactive advertisement  108  of  FIG. 1 , respectively. A non-interactive advertisement  308  may include, for example, a billboard, a sign, a television commercial, or any other advertisement that does not allow user interaction. Further, for example, the communication device  304  may include an exposure determiner  306  to identify that a user  312  is in a vicinity or proximity of a non-interactive advertisement  308 , whose location may be known, such as from an advertisement server/database  310  or from a channel to which a user  312  is tuned. The exposure determiner  306  may be the same as or similar to exposure determiner  101  ( FIG. 1 ). For instance, the exposure determiner  306  may get location information from a satellite-based or terrestrial network-based position-location system, and correlate the location with the known locations of advertisements within a certain range of the location in order to determine exposure duration  307 . For example, the range may vary depending on a visibility of the ad, e.g., a sign in a store window might have a first range smaller than a second range for a billboard. Also, the exposure determiner  306  can determine an amount of time, or exposure duration, that the user  312  is exposed to the non-interactive advertisement  308 . For example, the exposure determiner  306  can ascertain a duration of time spent stationery or travelling within range to see or hear a prominent non-interactive advertisement  308 . 
     Additionally, the system  300  includes a behavioral context determiner  314  that is able to identify one or more contextual information associated with the user, referred to as one or more behavioral context parameters  313 . For example, the one or more contextual information or behavioral context parameters  313  may include user movements over time, user interactions with the communication device  304  such as whether the user  312  is making a call or using a program on the communication device  304 , etc. Further, for example, the one or more behavioral context parameters  313  may further include population contextual information, such as information on what other users are doing relative to the non-interactive advertisement  308 , such as time spent in the vicinity of the non-interactive advertisement  308  or time spent viewing the non-interactive advertisement  308 . For example, the advertisement server/database  310  can receive location information from a population of handset subscribers that can be correlated with a database of advertisement customers (not shown). Alternatively or in addition, individual handsets may recognize proximity to a non-interactive advertisement  308  and make appropriate reporting to the advertisement server/database  310 . Moreover, the population contextual information may relate to all other users exposed to the non-interactive advertisement  308 , or a select group or subset of all other users, such as designated friends of the user. The behavioral context determiner  314  may be the same as or similar to behavioral context determiner  111  ( FIG. 1 ). 
     Further, the system  300  includes context components  316  that provide one or more behavioral context parameters  313  to the behavioral context determiner  314 . For example, the context components  316  may include, but are not limited to, other applications on the communication device  304 , such as a voice call application, a web browser, a Global Positioning System (GPS) or position/location application, a text messaging application, a media player application, etc. In addition, the context components  316  may include, but are not limited to, a database storing information related to what is happening in a vicinity of the communication device  304  at any given time. For example, such information may include, but is not limited to, automobile traffic information, local traffic control information such as presence of stop signs or stop lights and the state of a stop light, train information, venue information, or any other information that can help explain what is happening in a vicinity of the communication device  304 . As such, the behavioral context determiner  314  collects one or more behavioral context parameters  313  from the context components  316 , and based on the one or more behavioral context parameters  313 , or based on applying rules or algorithms to the one or more behavioral context parameters  313 , is able to determine a behavioral context  317  that describes what is happening on or in a vicinity of the communication device  304  at any given time. 
     Moreover, the system  300  includes an advertisement/context determiner or correlator  318  that determines whether a correlation  319  exists between the non-interactive advertisement  308  and the one or more behavioral context parameters  313 . The advertisement/context determiner or correlator  318  may be the same as or similar to correlator  101  ( FIG. 1 ). For example, the advertisement/context determiner or correlator  318  may include one or any combination of rules, heuristics, fuzzy logic, etc. for determining the correlation  319 . The correlation  319  represents that the user  312  is likely interested in the subject matter of the non-interactive advertisement  308 . In other words, the advertisement/context determiner or correlator  318  evaluates the exposure to a non-interactive advertisement  308 , with reference to one or more behavioral context parameters  313 , in order to determine whether user activities correspond to interest in the non-interactive advertisement  308 , or whether the user activities can be attributed to some other factor. For example, rather than interest in the non-interactive advertisement  308 , the one or more behavioral context parameters  313  may indicate that the user was waiting at a red light, or was stopped to make a voice call, rather than stopping in response to an interest in the product or service promoted by the non-interactive advertisement  308 . Accordingly, when the correlation  319  is determined to exist, the advertisement/context determiner or correlator  318  generates a trigger  320  to initiate obtaining of an interactive advertisement  302  corresponding to the non-interactive advertisement  308 , such as from a remotely-located source, including but not limited to the advertisement server/database  310 . For example, in an aspect, the interactive advertisement  302  allows a user  312  to interact with the interactive advertisement  302  on a user interface  324 , such as by clicking on links embedded with the interactive advertisement  302 , automatically dialing a phone number, etc. 
     In an aspect, the trigger  320 , which identifies the non-interactive advertisement  308  and the interested user  312  or user communication device  304 , is transferred across a communication network  326  and received by, for example, the advertisement server/database  310 . In some aspects, the advertisement server/database  310  includes an advertisement translator  328  that generates the interactive advertisement  302  corresponding to the non-interactive advertisement  308  in response to receiving the trigger  320 . In other aspects, the advertisement server/database  310  stores the interactive advertisement  302  with an identified relationship to the non-interactive advertisement  308 , and thus merely retrieves the interactive advertisement  302  from storage in response to receiving the trigger  320 , which may identify the non-interactive advertisement  308  or which includes parameters, such as location information, that allows identification of the non-interactive advertisement  308 . In any case, the advertisement server/database  310  transfers the interactive advertisement  302  across the communication network  326  for receipt by the communication device  304 , or for receipt by another device, such as a non-mobile or wired device, associated with the user  312 . For example, the destination of the interactive advertisement  302  may be determined based on where the user  312  is likely to act on the interactive advertisement  302 . 
     Thus, the system  300  provides apparatus and methods of delivering interactive advertisements  302  based on exposure to non-interactive advertisements  308  and taking into account one or more behavioral context parameters  313  that indicate a likelihood of user interest in the non-interactive advertisement  308 . 
     In one aspect, referring to  FIG. 4 , a methodology  400  is provided for targeted delivery of interactive advertisements based upon determining a user&#39;s apparent interest in a non-interactive advertisement, according to one aspect. An exposure by a user to a non-interactive advertisement is quantified at  401 . For example, the user is exposed to the non-interactive advertisement, such as but not limited to, receiving a mobile text message, proximity to a static or dynamic billboard, viewing an Internet Protocol Television (IPTV) pop-up, email, hearing an audio advertisement, or some other method. In one aspect, being in a certain retail facility is itself a non-interactive advertisement for certain goods and services. Since the media used for the non-interactive advertisement do not permit user feedback, the methodology determines sufficient exposure and applicable heuristic triggers in order to infer user interest in the non-interactive advertisement at  402 . Although the exposure is sufficient and heuristic triggers are indicative of user interest, a further evaluation can be made as to whether the user context validates or discounts the initial finding of interest in the non-interactive advertisement at  403 . With user context corroborating the interest, then an interactive advertisement corresponding to the non-interactive advertisement is accessed at  404 . This can be accomplished by creating an interactive advertisement corresponding to the non-interactive advertisement. The interactive advertisement is sent to the user via an appropriate device at  405 . For example, the interactive advertisement may be sent to a selected device associated with the user, and/or at a selected time, such as a time when it is likely that the user will be able to act on the interactive advertisement. Further, in an optional aspect, the effectiveness of the interactive advertisement can then be gauged at  406 . 
     Referring to  FIGS. 5 and 6 , the methodology of determining sufficient exposure and applicable heuristic triggers ( FIG. 4 ,  402 ) may vary, for example, depending on a type of non-interactive advertisement. 
     For example, in  FIG. 5 , one or more aspects of determining sufficient exposure and applicable heuristic triggers can be inferred with regard to user exposure to an audio and/or video type of non-interactive advertisement at  408 . The heuristic trigger to convert the audio and/or video non-interactive advertisement to an interactive advertisement can be based on one or more criteria, as described below. It should be appreciated, however, that the following list is illustrative and not all inclusive. 
     Sufficient exposure and applicable heuristic triggers may be determined for the audio and/or video non-interactive advertisement (e.g., radio, television) by performing one or more of the following evaluations: 
     (a) Determining that the audio and/or video content (non-interactive advertisement) is consumed in its entirety at  409 . In an aspect, for example, a given TV advertisement is watched in its entirety on a given TV channel and no TV advertisement is watched in its entirety immediately before or immediately after the given TV advertisement; 
     (b) Determining that the audio and/or video content has been consumed repeatedly at  410 . For example in the TV advertisement scenario, the given TV advertisement is watched more than once in its entirety on a given channel across different viewing times; 
     (c) Determining that the audio and/or video content has been consumed in its entirety across multiple channels, for example, in a give time period at  411 ; 
     (d) Determining that the audio and/or video content was actively replayed by the user at  412 . For example, the user pauses, rewinds and replays the given audio and/or video advertisement in its entirety; or 
     (e) Determining that the video content received a high rating by the user at  413 . For example, the user rates the given TV ad, using IPTV controls, with a high score, for example, while the given TV advertisement in progress. 
     Alternatively or in addition, the non-interactive advertisement may be a static content, e.g., billboard advertisement or retail signage. In these aspects, exposure may be linked more to the location of the user. In one aspect, such an advertisement is publicly viewed external to any mobile device carried by a user while the user is in transit. In another aspect, such an advertisement can be a static or static over a period of time. 
     For example, in  FIG. 6 , one or more aspects of determining sufficient exposure and applicable heuristic triggers can be inferred with regard to user exposure to the static type of non-interactive advertisement at  415 . The heuristic trigger to convert the static non-interactive advertisement to an interactive advertisement can be based on one or more of the following criteria: It should be appreciated, however, that the following list is illustrative and not all inclusive. 
     (a) Determining that the given user stood in close proximity of the billboard/store advertisement for a length of time that was greater than the average time spent by all users in the given area within a specified time period at  416 ; 
     (b) Determining that the given user stood in close proximity of the billboard/store advertisement for a length of time that was greater than the average time the given user spent anywhere else within a specified time period at  417 ; or 
     (c) Determining that the given user entered a store and stayed in the store or within a store aisle for a length of time that was greater than the average time spent by all users in the store/store aisle within a specified time period at  418 ; 
     The methodology of validating or discounting exposure time or heuristic triggers based upon one or more behavioral context parameters ( FIG. 4 , block  403 ) may include determinations to assess whether such behavioral context parameters correlate with user&#39;s interest to the non-interactive advertisement. Thus, the heuristic trigger could be conditioned by one or more of the following illustrative and not all inclusive criteria. 
     Referring to  FIG. 7 , in one aspect, the methodology ( FIG. 4 ,  403 ) may include determining a user context relative to others to validate or discount exposure and heuristic triggers at  420 . Determining a user context relative to others may include, but are not limited to, one or more of criteria relative to a general population at  421 , or criteria relative to a subset of the population at  427 . 
     Specific examples of criteria relative to a general population (block  421 ) may include, but are not limited to, scenarios such as: 
     (a) Determining if a lengthy stop occurred at a pedestrian crossing at  422 . For example, although all users stop at a given location due to physical characteristics such as a traffic light, stop sign, stop light, subway entrance, bus stop, etc., a given user exceeds the average time spent by other users at that location at a given time; 
     (b) Determining if user was travelling in an opposite direction at  423 . For example, a user is travelling in a direction that is opposite to the rest of the users in coming close to the physical advertisement can increase the likelihood of user interest; 
     (c) Determining if user paused by the non-interactive advertisement longer than typical for the general population at  424 . For example, the user pauses at a digital product placement longer than that by the general population; 
     (d) Determining that a user performed an action that is opposite of the general population&#39;s action (e.g., shows disinterest or lowers exposure interest score) at  425 ; or 
     (e) Determining if the user&#39;s presence in a neighborhood is associated with particular goods or services at  426 . For example, surroundings/neighborhood characteristics (e.g., travel agencies, diamond district, etc.) determine the user&#39;s interest to the associated advertisements as a population. 
     The criteria that may be evaluated to determine the user&#39;s behavior relative to a subset of a general population, such as a social network associated with the user at  427 , may include, but are not limited to, a determination as to a user&#39;s friends&#39; interests in relation to the non-interactive advertisement in order to infer a preference at  428 . For example, the user&#39;s friends may have expressed a strong interest in a given advertisement through user ratings and/or social recommendations, and such a preference may thereby be inferred to the user. 
     Continuing to  FIG. 8 , alternatively or in addition to the aspects described above in  FIG. 7 , determining one or more behavioral context parameters that validate or discount the exposure and heuristic triggers ( FIG. 4 ,  403 ) can be based on a user&#39;s usage or interactions with a wireless device at  430 . Such determinations may include, but are not limited to, one or more of: 
     (a) Determining whether the user is on a voice call at  431 . For example, determining the user is on a voice call while stopping by the advertisement or watching television; 
     (b) Determining whether the user was viewing/hearing a message at  432 . For example, the user gets a message (Short Message Service (SMS), Multimedia Messaging Service (MMS), email), and hence stopped by an advertisement or paused a p TV advertisement, to read the message on the phone. For example, a determination can be made based upon user inputs to a graphical user interface (GUI) that the user was sufficiently preoccupied with the SMS, MMS, or email not to be viewing the non-interactive advertisement; 
     (c) Determining whether the user was using a navigation aid at  433 . For example, the user is looking at a map on the phone to ensure the directions are right; 
     (d) Determining whether the user was using a camera at  434 . For example, the user is clicking a picture of a nearby site with the wireless device; 
     (e) Determining whether the user is using an application at  435 . For example, the user is using an application (e.g., game) on the phone; 
     (f) Determining whether the user has input a rating of the non-interactive advertisement at  436 . For example, the user provides a one-touch thumb-up-down response/intent, or a numerical or alphabetic rating, toward a given advertisement through the wireless device; 
     (g) Determining whether the user has an expressed mood at  437 . For example, the user&#39;s presence information based on the user&#39;s mood indicates “I am happy” as a status indicator; 
     (h) Determining the user&#39;s unexpressed mood at  438 . For example, detectable biometric triggers/body language—heart rate increase, dilated pupils, blood pressure change, etc., in aspects where the wireless device includes wireless health monitoring components; or 
     (i) Determining a user trajectory relative to the non-interactive advertisement at  435 . For example, the trajectory can be based on the user&#39;s velocity, knowing more about the user&#39;s exposure and line of sight, e.g. if the user is riding a bike, driving a car, walking, etc. at  435 . 
     Continuing to  FIG. 9 , alternatively or in addition to the aspects described above in  FIGS. 7 and 8 , determining one or more behavioral context parameters that validate or discount the exposure and heuristic triggers ( FIG. 4 ,  403 ) can include determinations based on history and/or a time window at  438 . Such determinations may include, but are not limited to, one or more of: 
     (a) Determining a repeated user action relating to the non-interactive advertisement over a period of time at  439 . For example, over a given time period, the user repeats the same action pertaining to the advertisement, such as stopping at the same location (e.g. to hear or view a static non-interactive advertisement), or pausing and replaying the advertisement on TV (e.g. to hear/view an audio/video non-interactive advertisement); or 
     (b) Determining that the user dislikes an advertisement at  440 . For example, the user Fast Forwards through the advertisement on TV repeatedly or avoids using a gift card/coupon from a store, indicating a lack of interest/compatibility with the advertisement; 
     Referring to  FIG. 10 , the methodology of sending an interactive advertisement corresponding to the non-interactive advertisement ( FIG. 4 ,  405 ) may vary, for example, depending on a device or time at which the user may be expected to be able to interact with the interactive advertisement. Such sending of the interactive advertisement may include, but is not limited to, one or more of: 
     (a) Delivering the interactive advertisement to another device at an expected location at  445 . For example, based on the user&#39;s velocity and direction, the user is on his way home, so instead of delivering the advertisement on the user&#39;s phone as a text message, the advertisement is delivered to the user&#39;s home computer as an email; 
     (b) Determining to delay or divert delivery at  446 . For example, if the user is in transit, such as on a flight, a text message including access to the interactive advertisement is queued to be sent to the user when the user lands. If the flight has a wireless connection, such as WiFi, the user may be provided an email with a link to the interactive advertisement; 
     (c) Delivering interactive content to the wireless device being used at  447 . For example, the user is using a media-shifting application like SLINGBOX of SKIFTA™ by QUALCOMM Incorporated of San Diego, Calif. to watch TV on his computer or mobile phone. The advertisement that the user is interested in is delivered to the device on which the show is being watched; or 
     (d) Determining a likelihood of being accessible at a given device at  448 . For example, a probability of being in front of a delivery device (home computer, mobile device, work computer) is modeled based on historical information relating to the user&#39;s mobility. 
     With benefit of the foregoing, the methodologies are capable of obtaining interactive advertisements when appropriately determined that passively exhibited interest has been demonstrated in a non-interactive advertisement. By some collaboration between, or sole efforts of, a mobile device or remote server, exposure is determined to a non-interactive advertisement. One or more behavioral context parameters are determined to correspond to the exposure to the non-interactive advertisement. The one or more behavioral context parameters include an exposure duration of the exposure to the non-interactive advertisement. It is determined whether a correlation exists between the non-interactive advertisement and the one or more behavioral context parameters. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. If the correlation exists, a trigger is generated to obtain an interactive advertisement corresponding to the non-interactive advertisement. 
     With reference to  FIG. 11 , illustrated is a system  500  for delivering advertisement to a user, according to one aspect. For example, system  500  can reside at least partially within a mobile device. It is to be appreciated that system  500  is represented as including functional blocks, which can be functional blocks that represent functions implemented by a computing platform, processor, software, or combination thereof (e.g., firmware). System  500  includes a logical grouping  502  of electrical components that can act in conjunction. For instance, logical grouping  502  can include an electrical component for determining exposure to a non-interactive advertisement  504 . Moreover, logical grouping  502  can include an electrical component for determining one or more behavioral context parameters corresponding to the exposure to the non-interactive advertisement  506 . The one or more behavioral context parameters include exposure duration of the exposure to the non-interactive advertisement. For another instance, logical grouping  502  can include an electrical component for determining whether a correlation exists between the non-interactive advertisement and the one or more behavioral context parameters  508 . The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. For an additional instance, logical grouping  502  can include an electrical component for generating a trigger to obtain an interactive advertisement corresponding to the non-interactive advertisement if the correlation exists  510 . Additionally, system  500  can include a memory  520  that retains instructions for executing functions associated with electrical components  504 ,  506 ,  508 , and  510 . While shown as being external to memory  520 , it is to be understood that one or more of electrical components  504 ,  506 ,  508  and  510  can exist within memory  520 . 
     With reference to  FIG. 12 , an exemplary computing environment  600  for implementing various aspects of the claimed subject matter includes a computer  612 , such as but not limited to a network server. The computer  612  includes a processing unit  614 , a system memory  616 , and a system bus  618 . The system bus  618  couples system components including, but not limited to, the system memory  616  to the processing unit  614 . The processing unit  614  can be any of various available processors. Dual microprocessors and other multiprocessor architectures also can be employed as the processing unit  614 . 
     The system bus  618  can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and/or a local bus using any variety of available bus architectures including, but not limited to, Industrial Standard Architecture (ISA), Micro-Channel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), Card Bus, Universal Serial Bus (USB), Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Firewire (IEEE 694), and Small Computer Systems Interface (SCSI). 
     The system memory  616  includes volatile memory  620  and nonvolatile memory  622 . The basic input/output system (BIOS), containing the basic routines to transfer information between elements within the computer  612 , such as during start-up, is stored in nonvolatile memory  622 . By way of illustration, and not limitation, nonvolatile memory  622  can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory  620  includes random access memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). 
     Computer  612  also includes removable/non-removable, volatile/non-volatile computer storage media.  FIG. 12  illustrates, for example, disk storage  624 . Disk storage  624  includes, but is not limited to, devices like a magnetic disk drive, floppy disk drive, tape drive, Jaz drive, Zip drive, LS-100 drive, flash memory card, or memory stick. In addition, disk storage  624  can include storage media separately or in combination with other storage media including, but not limited to, an optical disk drive such as a compact disk ROM device (CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RW Drive) or a digital versatile disk ROM drive (DVD-ROM). To facilitate connection of the disk storage devices  624  to the system bus  618 , a removable or non-removable interface is typically used such as interface  626 . 
     It is to be appreciated that the software described in  FIG. 12  acts as an intermediary between users and the basic computer resources described in the suitable computing environment  600 . Such software includes an operating system  628 . Operating system  628 , which can be stored on disk storage  624 , acts to control and allocate resources of the computer  612 . System applications  630  take advantage of the management of resources by operating system  628  through program modules  632  and program data  634  stored either in system memory  616  or on disk storage  624 . It is to be appreciated that the claimed subject matter can be implemented with various operating systems or combinations of operating systems. 
     In an aspect, for example, system applications  630  may include all or some portion of the exposure determiner  101 , the correlator  113 , and the behavioral context determiner  111 , as previously described in  FIG. 1 , for carrying out the functionality relating to determining interest in a non-interactive advertisement  108  and delivering a corresponding interactive advertisement  120 , as described herein. It should be understood, however, that the above-noted components may instead be part of the hardware of computing environment  600 , such as but not limited to being embodied in the processing unit  614 . 
     As shown in  FIG. 12 , a user enters commands or information into the computer  612  through input device(s)  636 . Input device(s)  636  include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processing unit  614  through the system bus  618  via interface port(s)  638 . Interface port(s)  638  include, for example, a serial port, a parallel port, a game port, and a universal serial bus (USB). Output device(s)  640  use some of the same type of ports as input device(s)  636 . Thus, for example, a USB port may be used to provide input to computer  612  and to output information from computer  612  to an output device  640 . Output adapter  642  is provided to illustrate that there are some output devices  640  like monitors, speakers, and printers, among other output devices  640 , which require special adapters. The output adapters  642  include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device  640  and the system bus  618 . It should be noted that other devices and/or systems of devices provide both input and output capabilities such as remote computer(s)  644 . 
     Computer  612  can operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s)  644 . The remote computer(s)  644  can be a personal computer, a server, a router, a network PC, a workstation, a microprocessor based appliance, a peer device or other common network node and the like, and typically includes many or all of the elements described relative to computer  612 . For purposes of brevity, only a memory storage device  646  is illustrated with remote computer(s)  644 . Remote computer(s)  644  is logically connected to computer  612  through a network interface  648  and then physically connected via communication connection  650 . Network interface  648  encompasses wire and/or wireless communication networks such as local-area networks (LAN) and wide-area networks (WAN). LAN technologies include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet, Token Ring and the like. WAN technologies include, but are not limited to, point-to-point links, circuit switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet switching networks, and Digital Subscriber Lines (DSL). 
     Communication connection(s)  650  refers to the hardware/software employed to connect the network interface  648  to the system bus  618 . While communication connection  650  is shown for illustrative clarity inside computer  612 , it can also be external to computer  612 . The hardware/software necessary for connection to the network interface  648  includes, for exemplary purposes only, internal and external technologies such as, modems including regular telephone grade modems, cable modems and DSL modems, ISDN adapters, and Ethernet cards. 
       FIG. 13  illustrates an exemplary communication system  700  having a configuration of hardware, software, and other resources of a mobile device  702 , consistent with one or more implementations of the present teachings. Mobile device  702  can include at least one antenna  704  (e.g., a transmission receiver or group of such receivers comprising an input interface, etc.) that receives a signal (e.g., pertaining to a mobile call initiation or other handshake, a handshake response, a mobile application data transfer, a data event, data event response, handshake termination, and so on) and a receiver  706 , which performs actions (e.g., filters, amplifies, down-converts, etc.) on the received signal. Antenna  704  can be further coupled to a transmitter  708  to transmit signals. Antenna  704  can for example transmit or receive a response to a handshake request, data event request, or the like. Transmitted or received signals can be or include a set of user activity information  710 , and other data, as described herein, such as information gleaned by the mobile device  702  or by the communication system  700  remote to the mobile device  702 , respectively. Antenna  704  and receiver  706  can also be coupled with a demodulator  712  that can demodulate received signals and provide the demodulated information to a processor  714  for processing. Mobile device  702  can additionally include memory  720  that is coupled to processor  714  and that can store data to be transmitted, received, and the like. 
     Processor  714  can analyze user activity information  710  received by antenna  704  or a user interface  716  of the mobile device  702  and/or generate user activity information  710  or other data for transmission by a transmitter  708  via a modulator  718 . Additionally, processor  714  can control and/or access one or more resources or components (e.g.,  722 ,  724 , etc.) of the mobile device  702 . Processor  714  can execute a runtime environment  722 , such as Brew® runtime environment available from QUALCOMM Incorporated, as well as one or more set of applications  724  or other software, modules, applications, logic, code, or the like. In one or more aspects, set of applications  724  can include client or user preferences  730  and/or other applications or resources. Also, in an aspect, for example, set of applications  724  can include all or some portion of the exposure determiner  101 , the correlator  113 , and the behavioral context determiner  111 , as previously described in  FIG. 1 , for carrying out the functionality relating to determining interest in a non-interactive advertisement  108  and delivering a corresponding interactive advertisement  120 , as described herein. It should be understood, however, that the above-noted components may instead be part of the hardware portion of mobile device  702 , such as but not limited to being embodied in processor  714 . Processor  714  can in one or more implementations communicate with a location module  726 , such as a Global Positioning System (GPS) module or chip, to receive and process location-related information, including location fixes for the user. Processor  714  can further communicate with a content service application programming interface (API)  728  to invoke catalog processing functions to execute function calls to extract user activity information  710  and perform other actions, according to the present teachings. Processor  714  can likewise couple with user interface  716 , such as a graphical user interface or other graphical display, to display non-interactive advertisement  108  ( FIG. 1 ) and/or interactive advertisement  120  ( FIG. 1 ), graphics, video, call-related data, user activity feeds as described herein, and other information. 
     In  FIG. 14 , a system  800  is depicted for using distributed sensors and processes including fixed infrastructure for delivering interactive advertisements deemed appropriate based upon exposure to non-interactive advertisements, according to one aspect. System  800  may also include a use case that involves distributing processing among different components in the system. 
     Consider, in one aspect, a user  802  who is in a first position  804  near to a first non-interactive advertisement  806 , depicted as on a vending machine  808 . Similarly, in another aspect, the user  802  can be detected as being at a second position  810  exposed to a second non-interactive advertisement  811 , depicted as at a retail store window  812 . These two aspects are discussed together below, however, it should be understood that each aspect may occur separately. 
     A surveillance camera system  814  with face recognition capability recognizes the user  802 , such as by accessing an employee biometric database  816 . Alternatively, a Radio Frequency Identifier (RFID) antenna  818  detects an employee identifier (ID) badge  820  carried by the user  802 . Alternatively or in addition, a mobile carrier  822  detects a GPS value transmitted by a WWAN mobile device  824  carried by the user  802 . The mobile carrier  822  can also detect a coarse location coordinate for the mobile device  824  that is correlated to being in proximity to the vending machine  808  or store window  812  based upon a sensor  827 . For example, the vending machine  808  detects that someone is standing in front of the device and the mobile carrier  822  can detect only one person that is in that area. The duration of exposure can be detected based upon a period of time in which a WLAN-capable device  825  carried by the user  802  is within the coverage area of an access point  826 . 
     An exposure determiner  828  detects exposure to the non-interactive advertisement  806  and/or  811 . For instance, a subroutine of an employee attendance tracking system  830  in a remote server  832  determines exposure to the non-interactive advertisement  806  and/or  811  by associating the user  802  to the location (position)  804  and/or  810  and to the non-interactive advertisement  806  and/or  811 , respectively. The exposure determiner  828  may be the same as or similar to exposure determiner  101  ( FIG. 1 ). Alternatively, this association can be performed solely by the respective device  824  and/or  825  carried by the user  802 . As a further alternative, the exposure determiner  828  can be distributed between the respective device  824  or  825  and the remote server  832 . 
     A behavioral context determiner  834  in the remote server  832  determines one or more behavioral context parameters, including exposure duration, corresponding to the exposure to the non-interactive advertisements  806  and/or  811 . The behavioral context determiner  834  may be the same as or similar to behavioral context determiner  111  ( FIG. 1 ). Alternatively, this context can be determined solely by the respective device  824  and/or  825  carried by the user  802 . As a further alternative, the exposure determiner  828  can be distributed between the respective device  824  or  825  and the remote server  832 . 
     A correlator  836  in the remote server  832  determines whether a correlation exists between the non-interactive advertisement  806  and/or  811  and the one or more behavioral context parameters. The correlation includes, at least in part, determining that the exposure duration achieves an exposure threshold. The correlator  836  may be the same as or similar to correlator  113  ( FIG. 1 ). The correlator  836  generates a trigger  838 . Alternatively, the correlation can be determined solely by the respective device  824  and/or  825  carried by the user  802 . As a further alternative, the exposure determiner  828  can be distributed between the respective device  824  or  825  and the remote server  832 . 
     A user interface  840  has a network interface  842  that obtains an interactive advertisement  844  corresponding to the non-interactive advertisement in response to the correlation existing as prompted by the trigger  838 . For example, a workstation  846  of the user can receive the interactive advertisement  844  pushed over a core network  848 . Alternatively, the device  824  carried by the user  802  can pull the interactive advertisement  844  from the mobile carrier  822 . 
     Variations, modification, and other implementations of what is described herein will occur to those of ordinary skill in the art without departing from the spirit and scope of the disclosure as claimed. Accordingly, the disclosure is to be defined not by the preceding illustrative description but instead by the spirit and scope of the following claims.