Abstract: A method and system for providing, to a user device configured for providing content to a user, one or more personalized content item recommendations. The method comprising: retrieving a seed content item identifier from user data stored in a user profile; using the seed content item identifier to generate a plurality of initial content item recommendations; sorting the plurality of initial content item recommendations based on the user profile; and providing one or more of the sorted content item recommendations as personalized content item recommendations to the user device.

Abstract: A computer-implemented method of targeting users based on content consumption comprises: for each of a plurality of users, monitoring user activity including identifying content selected for viewing by the users; 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 each user, the user record comprising or representing the user activity and/or the associated content metadata; and identifying users that have below a threshold level of user activity.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A computer-implemented method of determining affinity profiles, comprises: for each of a plurality of user devices, monitoring user activity including identifying television content selected for viewing by the user of the user device; obtaining metadata concerning the selected items of television content, the metadata representing at least some properties of the selected items of television 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.

Abstract: 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, 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; determine an audience that is expected to consume the selected item of content based on the affinity profiles of the users.

Abstract: 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.

Abstract: A computer-implemented method of determining household composition, the method, comprises: determining an affinity profile for a user based on a user record that represents television or other content selection and/or viewing by the user using at least one user device, wherein the user is a user account associated with a household and the method further comprises determining household composition based on the affinity profile for the user account, the 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.

Abstract: A computer-implemented method of using affinity profiles to obtain audience segments, 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; and categorizing each user into one or more of a plurality of user segments based on their affinity profile.

Abstract: 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.

Abstract: The method may include providing one or more content item recommendations, by opening a content recommendation session for a selected user, retrieving some user data for the selected user from a first storage resource, obtaining content information concerning content available from content sources, using the user data and the content information to generate a content item recommendation for the user and providing the content item recommendation to the user. The user data for the selected user may be stored at contiguous physical locations at the first storage resource.

Abstract: A method is disclosed for providing one or more content item recommendations, comprising opening a content recommendation session for a selected user; retrieving at least some user data for the selected user from a first storage resource; obtaining content information concerning content available from one or more content sources; using the user data and the content information to generate at least one content item recommendation for the user; and providing the content item recommendation to the user, wherein the user data for the selected user is stored at substantially contiguous physical locations at the first storage resource.

Abstract: A method for providing one or more content item recommendations for a user of a content distribution system having a plurality of users, comprises: opening a content recommendation session for a selected user; retrieving user data for the selected user from a first storage resource storing user data on a plurality of users, storing the user data in a second storage resource, and maintaining the user data in the second storage resource during the content recommendation session for the selected user; using the user data from the second storage resource and content information concerning content available from one or more content sources to generate at least one content item recommendation for the selected user during the content recommendation session for the selected user; and providing the at least one content item recommendation, wherein the method further comprises maintaining content recommendation sessions for a plurality of the users and maintaining in the second storage resource user data for said pl

Abstract: A computer-based method and apparatus for knowledge discovery from databases. The disclosed method involves the user creation of a project plan comprising a plurality of operational components adapted to cooperatively extract desired information from a database. In one embodiment, the project plan is created within a graphical user interface and consists of objects representing the various functional components of the overall plan interconnected by links representing the flow of data from the data source to a data sink. Data visualization components may be inserted essentially anywhere in the project plan. One or more data links in the project plan may be designated as caching links which maintain copies of the data flowing across them, such that the cached data is available to other components in the project plan. In one embodiment, compression technology is applied to reduce the overall size of the database.