System, computer program product, and method for automated gift determination and delivery

A system and method for automated gift determination and delivery is provided, which include identifying a contact from an electronic contact list for receiving a gift, detecting from first data related to the contact a change in an emotional state of the contact, validating from second data the change in the emotional state of the contact, and automatically selecting the gift from a plurality of identified gifts that is determined to be commensurate with the change status and a current emotional state of the contact.

BACKGROUND

The present invention relates to gift giving, and more specifically to gift giving based on the detection and analysis of an emotional state of a potential recipient of the gift.

It is well-known for people to be sensitive to another person's emotional state. When two people have a relationship, for example, friends or family members, and one of the people is sad or upset, it is often desirable for the other person to send flowers or other gifts to the unhappy person.

SUMMARY

An embodiment of the present invention relates to a method, and associated computer system and computer program product, for automated gift determination and delivery. A processor of a computer system identifies a contact from an electronic contact list for receiving a gift, detects from first data related to the contact a change in an emotional state of the contact, validates from second data the change in the emotional state of the contact; and automatically selects the gift from a plurality of identified gifts that is determined to be commensurate with the change in the emotional state and a current emotional state of the contact.

DETAILED DESCRIPTION

In brief overview, provided in some embodiments are a system and method for quickly and appropriately reacting to a change in emotional state of a contact, especially in cases where one person is at a remote location from a friend, family member, acquaintance, or other contact who experiences a change in an emotional state unbeknownst to the remote person but determined from data received by computer-based information sources and processed and analyzed to determine a particular gift commensurate with the emotional state of the identified contact. Some embodiments of the inventive concept provide a solution that provides automatic gift giving in situations where one person has not responded to another person such as a friend or family member who is a candidate for receiving a gift based on a detection and analysis of a change in emotional state of the other person. In some embodiments, the system and method determines when someone may be in need of encouragement, solace, or reassurance based on a substantial change in emotional state. In some embodiments, the system and method associates a confidence level to a reason for the change in emotional state. In some embodiments, the system and method allows the user to pre-approve a gift, gift recipient, consoling message, and/or other information in advance of providing the gift according to the intended recipient's emotional state. In some embodiments, a user pre-selects contacts who are eligible for possible gifts according to an automated gift system. This may include specific parameters, such as the maximum gift cost, frequency at which automated gift-giving may be performed, and so on.

In some embodiments, a gift, gift recipient, and/or gift message can be pre-approved, or otherwise selected, with a single action performed by a computer mouse, stylus, or the like that reduces the number or interactions needed to pre-approve a gift automatically identified by a gift selection and delivery system for a selected recipient determined according to data collected that is processed to establish a state of mind and/or emotional status change of the selected recipient.

For example, an email message may be generated and output to a user that includes a uniform resource locator (URL) that corresponds to an internet address or the like that receives a user's approval to provide a gift under predetermined conditions when the user selects the URL from a display. Here, a URL may be generated by the system in response to a determination of the emotional status change, a confirmation of a confidence level of the status change, and an identification of potential gifts, so that the user does not need to undergo the time-consuming steps of learning about the emotional state change and laborious gift-searching exercise. In another example, a pop-up notification may be displayed at the user's smartphone with a display button for approving a gift selection, e.g., using a mouse or touchscreen to select the button. In another example, a text message may be displayed on the user's smartphone requesting that the user approve a gift selection. In another example, a voice recording or computer-generated audio message from a computer device such as Google Home™ or Amazon Alexa™ may be output asking that the user provide a voice response regarding the approval of a gift selection. In another example, a telephone keypad from a smartphone or conventional telephone may be used to respond to an audio message, i.e., dual-tone multi-frequency (DTMF) signaling, from an automated phone call request approval of a gift selection. The concepts herein are not limited to these examples.

In some embodiments, the system and method provides a computing environment to quickly and accurately react to situations where a person may not learn of a change in emotional status of a friend, family member, coworker, and so on, but automatically reduces the time it takes to identify an appropriate gift and deliver it to that other person, for example, by providing a single-click feature for electronically performing this task, and to train the computer system to learn from previous events involving this gift recipient, from example, who may be prone to hyperbole-related emotions, and improve the accuracy of future determinations by an artificial intelligence system with respect to whether to send a gift under similar circumstances, whether to send a particular gift and/or message associated with the gift, and so on.

Referring to the drawings,FIG. 1depicts a block diagram of a gift selection and delivery system100as part of an overall system, in accordance with embodiments of the present invention. The gift selection and delivery system100is constructed and arranged to assess the emotional states of people or groups of people who may be candidates for receiving a gift initiated by a friend, family member, or other gift-giving person. The system100also provides for the ability for a user to pre-select contacts from a stored listing of contacts for receipt of a selected gift, which is automatically delivered to the contact according to an assessed emotional state and/or other established criteria. In addition to the gift selection and delivery system100, the overall system10may include a program executed at a user computer12, a data repository14, and various communication interfaces to third party computers, for example, described with reference to embodiments herein.

The gift selection and delivery system100includes a contact selector102, a system processor104, a sentiment and tone analyzer106, a confidence level determination module108, a gift selection module110, a notification module112, and a training module114. Some or all of these elements of the system may be part of a same hardware computer platform for example, executed by a common processor, or may be physically separate from each other, i.e., stored and executed by physically disparate hardware computer platforms, and in communication with each other via a data communication network16, e.g., a local area network (LAN) or a wide area network (WAN). In some embodiments, the gift selection and delivery system100includes a memory device or related computer readable storage device is coupled to one or more of the contact selector102, system processor104, sentiment and tone analyzer106, confidence level determination module108, gift selection module110, and notification module112. The storage device contains program code executable by the processor via the memory device to implement a method for automated gift determination and delivery, for example, method200ofFIG. 2or method300ofFIG. 3.

The contact selector102includes an input for receiving data regarding a selection of a contact. For example, a user can identify one or more contacts as potential recipients of a pre-approved gift. In some embodiments, a user can select on a user interface of a computer12a contact from the user's electronic contact list20, social listing of friends, profile or other data source that includes information about the user's friends, family members, business acquaintances, social circles, and so on. In some embodiments, the contact selector102can be preprogrammed so that one or more contacts in a particular grouping can be identified as automatic recipients of gifts. In some embodiments, the contact selector102incorporates or otherwise executes an application plugin, application programming interface (API), or other computer interface that establishes a data communication with an online social network computer website to retrieve data regarding potential gift recipients identified in the social network listing, and/or social media postings on the website, electronic communications such as email messages, text messages, and so on.

During operation, as shown inFIG. 4, the user can enter or otherwise select the name or identifier (401) of a potential recipient of a gift from the electronic contact list20. In response to the selection, the name of other identifier of the potential gift recipient is stored by the contact selector102locally or at the data repository14. In some embodiments, the social network contact list20is collocated with emotional state data corresponding to potential gift recipients of the contact list20at the data repository14.

The system processor104is configured to process received data regarding potential recipients selected from the contact list20as candidates for receiving gifts and facilitates the exchange of the processed data with the other components of the gift selection and delivery system100. For example, the system processor104can associate a potential gift recipient selected from the contact list20and corresponding information such as address, interests, family status, recently posted electronic messages on a social website, and so on with other relevant data, such as an e-commerce website where flowers, candy, or other gifts may be purchased. In some embodiments, the system processor104can generate a table, matrix, or the like that associates specific contacts with specific gifts, and further associates specific gifts with specific emotional states of a contact. For example, the system processor104may collect data that establishes that a particular potential gift recipient selected from the contact list20is the best friend of the user, and that this person enjoys a particular brand of chocolate candy. The system processor104can prepare a table that establishes this correlation.

The sentiment and tone analyzer106is configured to analyze the user's electronic contact list20, or more specifically, social media posts, text messages, or other data of potential gift recipients of the contact list20. Although a contact list20is shown inFIG. 1as being in communication with the user computer12via a network16, in some embodiments, the contact list20is electronically stored and executed at the user computer12. The sentiment and tone analyzer106can determine from this collected data a previous and/or current emotional state of a selected possible gift recipient and/or a change in emotional state of the selected possible gift recipient. Historical emotional state data can be compiled and stored at the data repository14for subsequent retrieval to determine confidence levels of emotional state changes, reasons for emotional state changes, and so on. In some embodiments, the sentiment and tone analyzer106can modify a registered emotional status in response to determined context data, changes in the emotional status, time delays, and so on.

In some embodiments, the sentiment and tone analyzer106includes a cognitive analyzer that includes an artificial intelligence system or is part of an artificial intelligence system that is capable of answering questions in the natural language and simulates of human thought processes in a computer model. The cognitive analyzer can execute a process, which can incorporate artificial intelligence technology to answer questions posed using a natural language and enabling definition of complex data analytics based on a corpus in which patterns and trends are setup and generated and can interact with a proposed solution. For example, the system may discern that a particular contact is sad because she lost her father. In doing so, the sentiment and tone analyzer106may collect and analyze historical decisions made by the system for training the computer system, for example, the artificial intelligence features of the system, to improve its accuracy for future decisions provided by the training module114, which processes a result of the sentiment and tone analyzer106for input to a knowledge base, data repository, machine learning, neural network, and/or artificial intelligence computer, for example, part of one or more elements of the computing architecture as shown inFIG. 1in order to train such computer elements by a direct output with respect to future decisions on gift determinations for identified recipients. For example, multiple iterations may be processed where for each iteration a specific gift is identified and the contextual data contributing to the decision to select the specific gift is stored at a database or the like and subsequently retrieved and output to the machine learning system for a next gift determination process.

The confidence level determination module108is configured to calculate a confidence level of the reason for a status change in a potential gift recipient's emotional state. For example, the confidence level determination module108may discern that a potential gift recipient is sad due to the death of her pet dog. In other embodiments, a reason for a potential gift recipient's emotional state, or the status of the change in emotional state, may not be determined due to a lack of information, whereby the confidence level determination module108calculates a probability of the confidence level on the reason for a status change in a potential gift recipient's emotional state without this information. In some embodiments, the confidence level determination module108includes a cognitive analyzer that provides artificial intelligence to determine from the collected data whether the contact has a tendency for hyperbolic emotions, whereby the system may determine not to send a gift but instead store this information to train the computer system to improve its accuracy for future decisions. An iteration process extending between these electronic elements of the system can improve a result calculated by the machine learning, neural network, and/or artificial intelligence computer, thereby training, updating, and optimizing the system to efficiently identify relevant gifts according to a high degree of accuracy with respect to the determined state of mind of the recipient.

The gift selection module110is configured to automatically identify a gift for a selected contact in response to a determination that a calculated confidence level is greater than a threshold value. As described above, a table, matrix, or the like may be generated and stored at the data repository14that identifies gifts associated with a particular contact. When the system determines an acceptable confidence level of a reason for a change in emotional state of the change, the gift selection module110can identify a gift from a listing of gifts or from the table, matrix, or the like that is commensurate with the type of emotional state, for example, happy, sad, angry, and so on. In some embodiments, a contact may not have a gift associated with the emotional state, or identified as a possible recipient of a gift. Here, the gift selection module110can receive and process data regarding other contacts and their gifts, and a gift may be identified from an analysis of this other data. For example, the gift selection module110may establish that the majority of people in a contact list are identified as receiving candy, clothing, sporting event tickets, and so on when it is determined that they are depressed. When a new contact is added to the list and is determined to be a male adult, this new contact can automatically be identified as receiving a baseball game tickets when he is depressed.

The notification module112is configured to generate and output a notification the user of the delivery of the gift and/or other information that is relevant to the gift delivery. For example, an email message can be provided to the user's computer12of an automatic delivery of a gift to a contact determined to be distraught over the death of a family member.

FIG. 2depicts a flow chart of a method200for automated gift delivery, in accordance with embodiments of the present invention. One embodiment of the method200or algorithm that may be implemented by incorporating some or all of the computing elements of the system described inFIG. 1, one or more computer systems as defined generically inFIG. 5.

At block202, a computer user selects on a user interface102of a mobile device, tablet, personal computer, or other computing device an identification of one or more people of interest who may be possible recipients of a gift provided by the user. The identification may be determined from personal contacts such as friends or family members listed in the user's electronic contact list20, or social network profile or other data source that stores contact information. The contacts are selected for possibly receiving future gifts. For example, referring again toFIG. 4, selected contacts (401) allow the system processor104to identify the contact as well as other information such as an address (402) of the contact to send a gift. In setting this up, the user can also set up a payment method (403), such as credit card information for automatically purchasing a gift when a contact is selected for actually receiving a gift. Other information such as a price limit (404) may be entered.

At block204, an emotional state of a selected possible gift recipient is determined by the sentiment and tone analyzer106and registered by the system processor104at the data repository14. The sentiment and tone analyzer106can access a social media website or the like to access information for analysis about an emotional state of a potential gift recipient of the contact list20. For example, the sentiment and tone analyzer106can determine from a recent message posted to a potential gift recipient's social media account22that the potential gift recipient announced her wedding engagement to a longtime boyfriend.

The sentiment and tone analyzer106can determine that the emotional state of the potential gift recipient is happy, ecstatic, and so on. The analyzer106can parse keywords from the message such as the name of the boyfriend, the date of the wedding proposal, and so on. This data can be used to identify an appropriate gift. In some embodiments, the keywords can be automatically inserted into a predetermined boilerplate language added to a card to be sent with the gift. The emotional state details may be stored at the data repository14for subsequent retrieval and use when determining confidence levels, a change in the emotional status, and so on.

In some embodiments, the sentiment and tone analyzer106can modify a registered emotional status in response to determined context data, changes in the emotional status, factors such as time delays, and so on. For example, a contact may be determined to be depressed for one month, where a context analyzer of the sentiment and tone analyzer106provides a determination in response to received context data that this contact should not receive a gift every day, whether the contact should receive an expensive gift, or whether a predetermined user-provided parameter is to be modified or bypassed if determined context data exceeds a threshold. In another example, the emotional status of a contact may change every week, where a determination is made that this contact should not receive a gift every week, but instead change the parameters so that the contact receives a gift once a month. In another example, a contact may have recently lost her job one week followed by the death of a parent the next week. Here, a gift is warranted for each of these events.

At block206, a determination is made whether a gift is warranted for the selected possible gift recipient in response to a determination and registration of the change in emotional state. For example, a potential gift recipient who is given to hyperbole may not receive any gift, regardless of emotional status. For example, historical data stored at the data repository14may reveal that a potential gift recipient tends to exaggerate his emotions, for example, posting messages exhibiting exhilarant behavior for trivial events. This determination can be made by comparing a current posting at the social media website22with previous postings and applying the analyzer106to determine trends, changes in patterns with respect to the tone of the social media postings, and so on.

At block208, the gift is approved for purchase and delivery to and receipt by the selected gift recipient. In some embodiments, the gift is automatically approved, with no user interaction. In other embodiments, user interaction is required, for example, selecting a URL in a received email message, a button in a pop-up notification or a text message on the user's mobile device, a voice notification from a computer-generated voice request, and so on.

At block210, the gift is selected according to the determined emotional state of the gift recipient. In some embodiments, the gift is selected according to a table, matrix, or the like that identifies specific gifts with specific emotional states of the gift recipient, for example, flowers selected for sadness, candy for love, and so on. Other approaches for selecting a gift may equally apply. In other embodiments, the system may electronically track a recipient's social media22to acquire data about the recipient's hobbies, and identify potential gifts based on this acquired data. For example, a contact's social media postings may suggest that the contact enjoys fine wine and sailing, where a gift may be selected that includes a particular brand of wine and/or a book on sailing. In other embodiments, the system may collect historical data on a user's gifts to establish the effectiveness of certain gifts with respect to changing an emotional state. For example, the sentiment and tone analyzer106may access the data repository14to collect data that establishes that a particular brand of chocolate went previously delivered to a contact resulted in a positive change in the contact's emotional state.

At block212, the selected gift is delivered to the selected gift recipient. In some embodiments, the selected gift can be automatically purchased via an e-commerce communication between the gift selection and delivery system100and a website or other online location where the gift can be purchased. Purchase data such as credit card information and so on can be retrieved from user information stored at the data repository14.

At block214, the user receives a notification, for example, an email message or text message, that is generated by the notification module112of the gift selection and delivery system100after the gift has been purchased and/or delivered. In some embodiments, a prerecorded typed, audio, and/or video message is stored at the data repository14and automatically retrieved by the notification module112for processing and output to a personal computer12of the user.

FIG. 3depicts a flow chart of a method300for configuring a special-purpose computer to associate a confidence level to a reason for a change in emotional state, in accordance with some embodiments. One embodiment of the method300or algorithm that may be implemented by incorporating some or all of the computing elements of the system described inFIG. 1, one or more computer systems as defined generically inFIG. 5.

At block302, a computer user selects on a user interface102of a mobile device, tablet, personal computer, or other computing device an identification of one or more people of interest who may be possible recipients of a gift provided by the user. The identification may be determined from personal contacts such as friends or family members listed in the user's electronic contact list20, or social network profile or other data source that stores contact information. The contacts are selected for possibly receiving future gifts. Selected contacts allow the system processor104to identify the contact as well as other information such as an address of the contact to send a gift. In setting this up, the user can also set up a payment method, such as credit card information for automatically purchasing a gift when a contact is selected for actually receiving a gift.

At block304, the user can enter into the computer display a set of gift criteria. For example, the user can enter a price limit on a gift, or a type of gift, or a particular gift for a selected contact. In some embodiments, names or other information of one or more gifts may be selected for a particular contact of interest to the user.

At block306, the user's electronic contact list, or more specifically, social media posts, text messages, or other accessible information displayed electronically on network-connected computers by the user's contacts is analyzed by the sentiment and tone analyzer106to ascertain individuals and identify data related to identified contacts, derive personality and behavioral traits, and so on.

At block308, a status change in one or more contacts is detected and validated. In some embodiments, the change in emotional state is determined by comparing prior social media posts made by the person of interest. For example, a derived profound or drastic change in emotional state in block306can be determined from a comparison of a current social media post that a selected contact had a death in the family to a previous post from the same contact that the contact had a pleasant day.

At block310, at least one of a probable cause and a confidence level of the reason for status change are calculated. The probable cause or likely reason for the status change is determined from data analyzed by the confidence level determination module108, for example, data collected about a past relationship status, posts, pictures, and so on of a relationship, a change in a user's profile from “in a relationship” to “single,” and other indications of a breakup in the relationship. The confidence level of the reason for the status change is determined by the same or similar data. However, additional data such as historical information may be processed, for example, by the analyzer106and/or confidence level determination module108, to establish the confidence level for the reason for a change in a particular emotional state. Referring to the previous example, the confidence level determination module108may calculate a 100% confidence level that a breakup occurred. Thus, embodiments provide for a confidence level that can be associated with an emotional state.

At block312, the system selects a gift that is determined by the system that the selected contact would appreciate. In some embodiments, the system determines the gift based on the contact profile and social media postings in addition to a reason for the change in emotional state. In other embodiments, the system relies on preconfigured options to determine the gift.

At decision diamond314, a determination is made by the confidence level determination module108whether the confidence level is within a pre-defined threshold, for example, 97%. The threshold value is stored in a computer memory and accessed by the confidence level determination module108when performing the comparison. The threshold value may be preconfigured at the factory, or configured by a user, for example, changed to a different value. If yes, then at block316the system generates and outputs a data signal to the gift selection module110and/or notification module112, which automatically notifies a source of the gift, for example, a retail store, flower shop, and so on, which may have a delivery service or otherwise send in response a request to a delivery service to deliver the gift selected at block312to the intended recipient. In some embodiments, a message can be automatically generated to be provided to the recipient with the gift. For example, in the previous example where a breakup is determined with a high degree of confidence, a bouquet of flowers can be automatically selected along with a note that includes a predetermined message, for example, “Today was a bad today but tomorrow will be better.” Predetermined messages can be recorded and stored at the data repository14, or other database remote from but in communication with the system.

If no, then the method proceeds to block320, where different actions or no action may be taken. In some embodiments, the system generates a status that is output to the user as a notification, for example, a previous status, a current status, details on a selected gift, or a combination thereof, then requests that the message recipient approve the receipt of the gift. The user may approve the gift by selecting a button, icon, or the like displayed on the user's computer12. In other embodiments, a generic gift such a flower bouquet or a greeting card may be selected along with a message, which may or may not require user approval.

In some embodiments, the content of the message generated by the notification module112varies depending on the confidence level value generated by the confidence level determination module108. For example, a determination may be made that a user's contact may have recently lost a parent based on the collected social media posts and/or other data. The system may generate a first message for delivery with a gift if the confidence level is greater than the threshold but less than 100% confidence, for example, “You are in our prayers.” However, The system may generate a second message if the confidence level is 100%, for example, “Sorry for your loss.” In this example, the 100% confidence level may be established by an analysis of a combination of recent media postings stating “It has been a rough day. Dad went on life support” and “Dad has taken a turn for the worse” combined with a current posting that states “RIP Dad.”

In another example, a determination made be made that a contact recently started a new job. Here, the system may generate a first message for delivery with a gift if the confidence level is greater than the threshold but less than 100% confidence, for example, “I am so happy for you.” However, the system may generate a second message if the confidence level is 100%, for example, “Congratulations on your new job.” In these examples, the confidence level is determined from collected social media posts and/or other data that establishes the degree of confidence, whereby the message is determined by the confidence level.

FIG. 5illustrates a block diagram of a computer system500that may be included in the system ofFIG. 1and the methods illustrated inFIGS. 2 and 3in accordance with the embodiments of the present disclosure. The computer system500may generally comprise a processor591, an input device592coupled to the processor591, an output device593coupled to the processor591, and memory devices594and595each coupled to the processor591. The input device592, output device593and memory devices594,595may each be coupled to the processor591via a bus. Processor591may perform computations and control the functions of computer500, including executing instructions included in the computer code597for the tools and programs capable of implementing a method, in the manner prescribed by one or more elements of the system and methods described with respect toFIGS. 1-4, wherein the instructions of the computer code597may be executed by processor591via memory device595. The computer code597may include software or program instructions that may implement one or more algorithms for implementing the methods of providing a result, as described in detail above. The processor591executes the computer code597. Processor591may include a single processing unit, or may be distributed across one or more processing units in one or more locations (e.g., on a client and server).

The memory device594may include input data596. The input data596includes any inputs required by the computer code597. The output device593displays output from the computer code597. Either or both memory devices594and595may be used as a computer usable storage medium (or program storage device) having a computer readable program embodied therein and/or having other data stored therein, wherein the computer readable program comprises the computer code597. Generally, a computer program product (or, alternatively, an article of manufacture) of the computer system500may comprise said computer usable storage medium (or said program storage device).

Memory devices594,595include any computer readable storage medium, including those described in detail below. In one embodiment, cache memory elements of memory devices594,595may provide temporary storage of at least some program code (e.g., computer code597) in order to reduce the number of times code must be retrieved from bulk storage while instructions of the computer code597are executed. Moreover, similar to processor591, memory devices594,595may reside at a single physical location, including one or more types of data storage, or be distributed across a plurality of physical systems in various forms. Further, memory devices594,595can include data distributed across, for example, a local area network (LAN) or a wide area network (WAN). Further, memory devices594,595may include an operating system (not shown) and may include other systems not shown inFIG. 6.

In some embodiments, the computer system500may further be coupled to an Input/output (I/O) interface and a computer data storage unit. An IVO interface may include any system for exchanging information to or from an input device592or output device593. The input device592may be, inter alia, a keyboard, a mouse, etc. or in some embodiments the sensors110. The output device593may be, inter alia, a printer, a plotter, a display device (such as a computer screen), a magnetic tape, a removable hard disk, a floppy disk, etc. The memory devices594and595may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc. The bus may provide a communication link between each of the components in computer500, and may include any type of transmission link, including electrical, optical, wireless, etc.

An IVO interface may allow computer system500to store information (e.g., data or program instructions such as program code597) on and retrieve the information from computer data storage unit (not shown). Computer data storage unit includes a computer-readable storage medium, which is described below. In one embodiment, computer data storage unit may be a non-volatile data storage device, such as a magnetic disk drive (i.e., hard disk drive) or an optical disc drive (e.g., a CD-ROM drive which receives a CD-ROM disk). In other embodiments, the data storage unit may include a knowledge base or data repository, for example, part of one or more elements of the computing architecture as shown inFIG. 1.

As will be appreciated by one skilled in the art, in a first embodiment, the present invention may be a method; in a second embodiment, the present invention may be a system; and in a third embodiment, the present invention may be a computer program product. Any of the components of the embodiments of the present invention can be deployed, managed, serviced, etc. by a service provider that offers to deploy or integrate computing infrastructure with respect to cognitive computer systems and methods. Thus, an embodiment of the present invention discloses a process for supporting computer infrastructure, where the process includes providing at least one support service for at least one of integrating, hosting, maintaining and deploying computer-readable code (e.g., program code597) in a computer system (e.g., computer500) including one or more processor(s)591, wherein the processor(s) carry out instructions contained in the computer code597Another embodiment discloses a process for supporting computer infrastructure, where the process includes integrating computer-readable program code into a computer system including a processor.

The step of integrating includes storing the program code in a computer-readable storage device of the computer system through use of the processor. The program code, upon being executed by the processor, implements a method of automated gift determination, gift selection according to an intended recipient's emotional state, and so on. Thus, the present invention discloses a process for supporting, deploying and/or integrating computer infrastructure, integrating, hosting, maintaining, and deploying computer-readable code into the computer system500, wherein the code in combination with the computer system500is capable of performing a method for providing an availability recommendation.

A computer program product of the present invention comprises one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement the methods of the present invention.

Characteristics are as follows:

Service Models are as follows:

Deployment Models are as follows: