ThinkAnalytics Ltd.

A computer-implemented method for obtaining one or more recommendation candidates for items of content available via a content distribution system, the method comprising: obtaining user data for a selected user, wherein the user data comprise or represent content metadata associated with user activity; performing a content recommendation process using the user data and content information for the available content to generate one or more initial content recommendation candidates for the user; generating or otherwise obtaining relationship information for the available content items and/or metadata associated with the available content items; generating one or more further content recommendation candidates from the initial content recommendation candidates using the relationship information.

A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content at one or more selected time periods, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; monitoring consumption of items of content or other activity of the users for different time periods; determine the likelihood of, or an expected audience measure for, the selected item of content being consumed during the or each selected time period based on the affinity profiles and the monitored consumption of content or other activity for the different time periods.

A computer-implemented method of determining an affinity profile for a temporary and/or anonymous user of a content distribution system, comprises: monitoring activity of the temporary and/or anonymous user comprising identifying content selected for viewing by the user; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

A computer-implemented method of determining affinity profiles, comprises: for each of a plurality of user devices, monitoring user activity including identifying content selected for viewing by the user of the user device; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating or updating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

A computer-implemented method and system for generating a synopsis for a content item comprising: obtaining user data for at least one user and/or associated metadata, wherein the user data and/or associated metadata is based on user activity for the at least one user; receiving content metadata and/or other content information for the content item; generating or otherwise obtaining a synopsis for the content item based on the obtained content information and based on at least some of said obtained user data.

A computer-implemented method for generating text data comprising a descriptor for a group of content of items, the method comprising: obtaining content metadata associated with a group of content items; generating a descriptor for the group of content items based on at least the content metadata associated with the group; at least one of displaying and storing the generated descriptor.

A content selection interface configuration system for configuring a content selection interface allowing user selection of content presented for viewing, the content selection interface configuration system configured to: provide one or more groups of content, each group of content including a plurality of content items; obtain data indicating at least one property of the content items of each group of content; obtain user activity including interactions by the user with content on a content selection interface; and determine a score each group of content of the plurality of groups of content based at least in part on the user activity of that user and the data indicating the at least one property of some or all of the content, wherein the score is indicative of a likely interest of the content in that group of content to one or more users of the content selection interface.

A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected content item type, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; monitoring consumption of selected items of content of the selected type to determine which of the users consumed the items of content of the selected type; determine an audience that is expected to consume the items of content of the selected type based on the affinity profiles of the users that were determined to have consumed the selected items of content.

A computer-implemented method and system for creating a channel schedule for a linear broadcasting content provider, is disclosed. The method comprises: obtaining metadata associated with a plurality of content items in a content catalogue, the metadata representing at least some properties of the content items; segmenting the plurality of content items into segments based on metadata similarity; creating one or more channels based on the segments; and scheduling the plurality of content items, in the respective segments, for the one or more channels.

A method of managing storage of user data of a content recommendation system is provided. The content recommendation system comprises a user learning module for receiving data indicative of user actions, determining one or more learn actions based on the received data and storing the learn actions on a storage resource. The method comprises determining a parameter associated with aging out a learn action stored on a storage resource of a content recommendation system. The learn action determined based on data indicative of a user action. The method further comprises aging out the learn action stored on the storage resource based on the parameter.