Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing recommendations based on social network sharing activity. Sharing activity relating to the sharing of the content item on a social network by a first user is accessed. Consumption information related to the consumption of the content item. A correlation between the sharing activity and the consumption information is determined. A recommendation is then generated based on the correlation.

Abstract: A machine may he configured to perform image evaluation of images depicting items for sale and to provide recommendations for improving the images depicting the items to increase the sales of the items depicted in the images. For example, the machine accesses a result of a user behavior analysis. The machine receives an image of an item from a user device. The machine performs an image evaluation of the received image based on an analysis of the received image and the result of the user behavior analysis. The performing of the image evaluation may include determining a likelihood of a user engaging in a desired user behavior in relation to the received image. Then, the machine generates, based on the evaluation of the received image, an output that references the received image and indicates the likelihood of a user engaging in the desired behavior.

Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing recommendations based on social network sharing activity. Sharing activity relating to the sharing of the content item on a social network by a first user is accessed. Consumption information related to the consumption of the content item. A correlation between the sharing activity and the consumption information is determined. A recommendation is then generated based on the correlation.

Abstract: A user activity detection engine monitors user activity during user sessions on a publication system, and detects a change in the level of the activity of the user that predicts that the user is about to execute a transaction. The change may be an increase in the level of activity. When the user activity detection engine detects such a change, the system may make an intervention to provide personalized marketing content for display to the user in an effort to improve the probability that the user will execute a transaction, and/or also to motive the user to execute the transaction on the system site instead of moving to a competitor site in search of a different transaction.

Abstract: A machine may be configured to perform image evaluation of images depicting items for online publishing. For example, the machine performing a user behavior analysis based on data pertaining to interactions by a plurality of users with a plurality of images pertaining to a particular type of item. The machine determines, based on the user behavior analysis, that a presentation type associated with one or more images of the plurality of images corresponds to a user behavior in relation to the one or more images. The machine determines that an item included in a received image is of the particular type of item. The machine generates an output for display in a client device. The output includes a reference to the received image and a recommendation of the presentation type for the item included in the received image, for publication by a web server of a publication system.

Abstract: A machine is configured to determine fashion preferences of users and to provide item recommendations based on the fashion preferences. For example, the machine accesses an indication of a fashion style of a user. The fashion style is determined based on automatically captured data pertaining to the user. The machine identifies, based on the fashion style, one or more fashion items from an inventory of fashion items. The machine generates one or more selectable user interface elements for inclusion in a user interface. The one or more user interface elements correspond to the one or more fashion items. The machine causes generation and display of the user interface that includes the one or more selectable user interface elements. A selection of a selectable user interface element results in display of a combination of an image of a particular fashion item and an image of an item worn by the user.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. Consistent with some embodiments, the method may include receiving a request to generate a message, which in an example embodiment is to be published to a social network platform. In response to receiving the request, a generative grammar model defining the structure of the message is accessed. The generative grammar model may include a number of blanks and may specify a source along with a grammatical constraint for a term to populate each blank. The method may further include generating the message in accordance with the generative grammar model, and causing the generated message to be published.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. Consistent with some embodiments, the method may include receiving a request to generate a message, which in an example embodiment is to be published to a social network platform. In response to receiving the request, a generative grammar model defining the structure of the message is accessed. The generative grammar model may include a number of blanks and may specify a source along with a grammatical constraint for a term to populate each blank. The method may further include generating the message in accordance with the generative grammar model, and causing the generated message to be published.

Abstract: A machine may be configured to determine fashion preferences of users and to provide item recommendations to the users based on the users' fashion preferences. For example, the machine receives an image of a user and a set of spatial data indicating a position of the body of the user in a three-dimensional space. The machine may perform an analysis of the image and the set of spatial data. The performing of the analysis may include extracting, from the image, an image swatch that depicts a portion of an item worn by the user. The machine may identify a fashion preference of the user based on the analysis of the image and of the set of spatial data. The machine may identify an item that corresponds to the fashion preference of the user within an inventory of fashion items and may generate a recommendation of the identified fashion item.

Abstract: Systems and methods are presented for generating recommendations using multi-level social network analysis of user behavior. In some embodiments, the system receives a set of user interactions, from a plurality of users, performed on a set of data objects; generates a set of associations between the set of data objects; and identifies a set of data object clusters indicative of the set of associations. The system generates an organization of the set of data objects based on the set of associations and the set of data object clusters and causes presentation of a plurality of data objects of the set of data objects on a user interface of a user device based on the organization.

Abstract: Systems and methods are presented for generating recommendations using multi-level social network analysis of user behavior. In some embodiments, the system receives a set of user interactions, from a plurality of users, performed on a set of data objects; generates a set of associations between the set of data objects; and identifies a set of data object clusters indicative of the set of associations. The system generates an organization of the set of data objects based on the set of associations and the set of data object clusters and causes presentation of a plurality of data objects of the set of data objects on a user interface of a user device based on the organization.

Abstract: Systems and methods are presented for evaluating and incorporating a plurality of input streams into a single input stream. In some embodiments, the system generates a first set of recommendations provided by a plurality of input streams and receives one or more selections of recommendations from the first set of input streams. The system determines a session intent based on the one or more selections and selects a set of input streams, from the plurality of input streams, corresponding to the one or more selection and the session intent. The system generates a second set of recommendations using the set of input streams and the session intent and causes presentation of the second set of recommendations on a user interface of a user device.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. Consistent with some embodiments, the method may include receiving a request to generate a message, which in an example embodiment is to be published to a social network platform. In response to receiving the request, a generative grammar model defining the structure of the message is accessed. The generative grammar model may include a number of blanks and may specify a source along with a grammatical constraint for a term to populate each blank. The method may further include generating the message in accordance with the generative grammar model, and causing the generated message to be published.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for creating messages using generative grammar models is presented. Consistent with some embodiments, the method may include receiving a request to generate a message, which in an example embodiment is to be published to a social network platform. In response to receiving the request, a generative grammar model defining the structure of the message is accessed. The generative grammar model may include a number of blanks and may specify a source along with a grammatical constraint for a term to populate each blank. The method may further include generating the message in accordance with the generative grammar model, and causing the generated message to be published.

Abstract: Software authenticates a first user of a first mobile device and a second user of a second mobile device. Each user agrees or has previously agreed to share video data captured by the user with other authenticated users. The software determines whether the first mobile device is located proximate to the second mobile device. Then the software receives video data captured by the second mobile device and transmits the video data to the first mobile device for display along with an annotation, if the first mobile device is proximate to the second mobile device. The annotation indicates the location of the second mobile device relative to the first mobile device and includes data as to camera angle of the second mobile device received from the second mobile device. The software persistently stores the video data upon receipt of a command from the user of the first mobile device.

Abstract: A machine may be configured to perform image evaluation of images depicting items for online publishing. For example, the machine performing a user behavior analysis based on data pertaining to interactions by a plurality of users with a plurality of images pertaining to a particular type of item. The machine determines, based on the user behavior analysis, that a presentation type associated with one or more images of the plurality of images corresponds to a user behavior in relation to the one or more images. The machine determines that an item included in a received image is of the particular type of item. The machine generates an output for display in a client device. The output includes a reference to the received image and a recommendation of the presentation type for the item included in the received image, for publication by a web server of a publication system.

Abstract: A machine may be configured to perform image evaluation of images depicting items for sale and to provide recommendations for improving the images depicting the items to increase the sales of the items depicted in the images. For example, the machine accesses a result of a user behavior analysis. The machine receives an image of an item from a user device. The machine performs an image evaluation of the received image based on an analysis of the received image and the result of the user behavior analysis. The performing of the image evaluation may include determining a likelihood of a user engaging in a desired user behavior in relation to the received image. Then, the machine generates, based on the evaluation of the received image, an output that references the received image and indicates the likelihood of a user engaging in the desired behavior.

Abstract: Software authenticates a first user of a first mobile device and a second user of a second mobile device. Each user agrees or has previously agreed to share video data captured by the user with other authenticated users. The software determines whether the first mobile device is located proximate to the second mobile device. Then the software receives video data captured by the second mobile device and transmits the video data to the first mobile device for display along with an annotation, if the first mobile device is proximate to the second mobile device. The annotation indicates the location of the second mobile device relative to the first mobile device and includes data as to camera angle of the second mobile device received from the second mobile device. The software persistently stores the video data upon receipt of a command from the user of the first mobile device.

Abstract: Systems and methods are presented for generating recommendations using multi-level social network analysis of user behavior. In some embodiments, the system receives a set of user interactions, from a plurality of users, performed on a set of data objects; generates a set of associations between the set of data objects; and identifies a set of data object clusters indicative of the set of associations. The system generates an organization of the set of data objects based on the set of associations and the set of data object clusters and causes presentation of a plurality of data objects of the set of data objects on a user interface of a user device based on the organization.

Abstract: Systems and methods are presented for evaluating and incorporating a plurality of input streams into a single input stream. In some embodiments, the system generates a first set of recommendations provided by a plurality of input streams and receives one or more selections of recommendations from the first set of input streams. The system determines a session intent based on the one or more selections and selects a set of input streams, from the plurality of input streams, corresponding to the one or more selection and the session intent. The system generates a second set of recommendations using the set of input streams and the session intent and causes presentation of the second set of recommendations on a user interface of a user device.