Systems and methods are provided for dynamically generating a product description personalized for a target user account. Product description data and/or product comment data associated with the product are obtained from a server via a communication network. Based on the product description data and/or product comment data, a product description template, comprising fields to be populated, is generated and stored in memory. Comment data associated with a product of interest is obtained from a server via the network. The comment data originates from a set of user accounts each having a similarity score with a target user account that is above a similarity threshold. Based on the set of comment data, comment-based description data are generated and stored in memory. Based on the product description template and the comment-based description data, a product description is generated for presentation for the target user account.

A customer profiling system and method are described. The system comprises a receiver for receiving event trigger data in response to a customer interacting with an environment; a processor configured to: uniquely determine customer identifier data associated with the event trigger data; and to associate the event trigger data with a customer profile associated with the unique customer identifier.

Sensor data analysis may include obtaining video data, detecting facial data within the video data, extracting the facial data from the video data, detecting indicator data within the video data, extracting the indicator data from the video data, transforming the extracted facial data into representative facial data, and determining a mood of the person by associating learned mood indicators derived from other detected facial data with the representative facial data. The analysis may include determining that the representative facial data is associated with a complex profile, and determining a context regarding the person within the environment by weighting and processing the determined mood, at least one subset of data representing information about the person of the complex profile, and the indicator data. The analysis may include determining a user experience for the person, and communicating the determined user experience to a device associated with the person.

An online system automatically and dynamically determines an audience for content by clustering users across various dimensions, and refining targeting criteria for the content. The online system receives content and initial targeting criteria from a content provider. The content is provided to a group of users that meet the initial targeting criteria. The system collects content response data from the group of users that were provided the content, including user responses to the content and dynamic data relating to time and location of the user responses. The content response data is further integrated with user characteristics, content presentation data, and social response data to generate integrated user-content data of the content. Clusters of users are generated based on features of the integrated user-content data, and refined targeting criteria are identified based on the generated clusters that can then be used for more accurate targeting of the content to users.

In an automatic, computer-implemented method, a selected television advertisement is presented automatically in association with a television program or channel, which in turn is selected based at least in part on information from an online user profile that contains information indicating a user's preference for that television program or channel. The television advertisement is selected based at least in part on additional information from the online user profile that is unrelated to the selected television program or channel. The selected television advertisement is presented on or during the selected television program or channel via a set-top box, which has a set-top box identifier associated with the online user profile.

A computer-implemented method for controlling content distribution includes forwarding information associated with a user to a device operated by the user, the information being configured for use in selecting content from any of multiple content providers for a content distribution to the user. The method includes receiving, in response to the information, an edit of the information forwarded from the device. The edit identifies a first content provider and including a first modification of the content distribution regarding the first content provider. The method includes storing the edit in association with the information such that the first modification is taken into account in the content distribution. The method can be implemented using a computer program product tangibly embodied in a computer-readable storage medium.

A system that is capable of receiving and interpreting a user's spoken commands is also coupled to a television interface device that controls video programming content displayed the user's television. The user can speak commands to cause certain programs to be played, and to control various functions of the television. The system can track and analyze a user's video viewing habits. In addition, the system is able to determine which of multiple users might be interested in a particular video program, and the system can play marketing messages regarding that video program to those users that might be interested in viewing the video program.

Disclosed herein are aspects associated with contextual, or related, media enrichment presentation item of a media object served via the internet. A request to annotate a media object in connection with the media object's presentation is received, and a media object identifier and a profile identifier are obtained. The media object's information is retrieved using the media object identifier, and a profile is retrieved using the profile identifier. A response including one or more references to one or more media enrichment presentation items is transmitted, each reference to a media enrichment presentation item comprising information for use in retrieving the media enrichment presentation item for presentation in connection with presentation of the media object.

A method, system, and non-transitory computer-readable record medium for providing chatroom embedded content are provided. The method implemented by a computer system including at least one processor configured to execute computer-readable instructions stored in a memory, includes receiving a request for entering a chatroom; and displaying content related to the chatroom based on a system message of the chatroom in response to entering the chatroom.

A computer-implemented method for providing a personalized interface to a user based on whether the user is serious about making a purchase may include: obtaining customer identification data and customer input data a customer, wherein the customer input data comprises a request from the customer; determining a request status of the customer based on the customer identification data and the customer input data; obtaining customer interface activity data of the customer based on the request status; obtaining customer purchasing data of the customer based on the request status; generating a prediction model based on the customer interface activity data and the customer purchasing data; training the generated prediction model by classifying the customer based on the customer interface activity data and the customer purchasing data; obtaining user identification data and user interface activity data of a user via a user device, the user interface activity data indicating interactive activities between the user and a user interface displayed on the user device; determining a rating of the user to purchase a product based on the user identification data, the user interface activity data, and the prediction model; and providing, to the user, an updated user interface on the user device based on the determined rating.