Abstract: A method of segmenting relative user preferences into fine-grain and coarse-grain collections is provided. The method includes providing a set of content items having associated descriptive terms. The method also includes receiving user search input and, in response thereto, presenting a subset of content items. The method includes receiving user selection actions and analyzing the selections to learn the user's preferred descriptive terms. The method includes expressing the learned preferred descriptive terms as a segmented probability distribution function having at least one fine grain segment and at least one coarse grain segment. In response to subsequent search input, the method calls for selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented probability distribution function.

Abstract: A method of segmenting relative user preferences into fine-grain and coarse-grain collections is provided. The method includes providing a set of content items having associated descriptive terms. The method also includes receiving user search input and, in response thereto, presenting a subset of content items. The method includes receiving user selection actions and analyzing the selections to learn the user's preferred descriptive terms. The method includes expressing the learned preferred descriptive terms as a segmented probability distribution function having at least one fine grain segment and at least one coarse grain segment. In response to subsequent search input, the method calls for selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented probability distribution function.

Abstract: A method of segmenting relative user preferences into fine-grain and coarse-grain collections is provided. The method includes providing a set of content items having associated descriptive terms. The method also includes receiving user search input and, in response thereto, presenting a subset of content items. The method includes receiving user selection actions and analyzing the selections to learn the user's preferred descriptive terms. The method includes expressing the learned preferred descriptive terms as a segmented probability distribution function having at least one fine grain segment and at least one coarse grain segment. In response to subsequent search input, the method calls for selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented probability distribution function.

Abstract: A method of segmenting relative user preferences into fine-grain and coarse-grain collections is provided. The method includes providing a set of content items having associated descriptive terms. The method also includes receiving user search input and, in response thereto, presenting a subset of content items. The method includes receiving user selection actions and analyzing the selections to learn the user's preferred descriptive terms. The method includes expressing the learned preferred descriptive terms as a segmented probability distribution function having at least one fine grain segment and at least one coarse grain segment. In response to subsequent search input, the method calls for selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented probability distribution function.

Abstract: A user-interface method of selecting and presenting a collection of content items based on user navigation and selection actions associated with the content is provided. The method includes associating a relevance weight on a per user basis with content items to indicate a relative measure of likelihood that the user desires the content item. The method includes receiving a user's navigation and selections actions for identifying desired content items, and in response, adjusting the associated relevance weight of the selected content item and group of content items containing the selected item. The method includes, in response to subsequent user input, selecting and presenting a subset of content items and content groups to the user ordered by the adjusted associated relevance weights assigned to the content items and content groups.

Abstract: Methods of and systems for selecting and presenting content based on user identification are provided. A user-interface method of selecting and presenting content items in which the presentation is ordered at least in part based on inferring which user of a collection of users is using an input device includes providing a set of content items, providing a set of preference information for each user indicating content item preferences of a corresponding user, and providing a set of user keypress biometric models representing expected keypress activity for the corresponding user. User keypress activity to identify desired content items is monitored to biometrically characterize the user and analyzed to find the closest match to one of the keypress biometric models. Based on the closest match, which user of the collection of users entered the input is inferred and the corresponding preference information is used to select, order, and present content items.

Abstract: A method of selecting and presenting content based on inferred user preferences is provided. The method includes providing a set of content items having associated descriptive terms and receiving search inputs from an input device and presenting a corresponding subset of content items. The method includes receiving selection actions of content items and analyzing the descriptive terms associated with the selected content items to learn a composite set of preferred descriptive terms of the plurality of users of the input device. The method includes inferring preferences of individual users from the composite set of preferred descriptive terms by decomposing the composite set of preferred descriptive terms into individual sets of preferred descriptive terms. The decomposition act utilizes prespecified statistical models of preferences.

Abstract: A method of and system for enhanced local-device content discovery is disclosed. A method includes providing a local collection of content items and associated metacontent on a device. The metacontent describes the informational content of the corresponding content items. A remote catalog of metacontent items and information describing relationships between the metacontent items is provided. Input is received from the user for finding at least one desired content item and a search query is formed including at least one metacontent item of the remote catalog based on matching the input from the user with metacontent items of the catalog and further based on the information describing relationships between the metacontent items. A subset of content items of the local collection associated with metacontent that at least partially matches the search query is selected and presented on a display device based on at least one ranking criterion.

Abstract: A method of and system for updating locally cached content descriptor information is disclosed. A method includes providing a remote catalog of metacontent associated with content items that describes their informational content. The method also includes providing a local collection of content items and associated metacontent. The method further includes, updating the metacontent associated with the content items of the local collection with metacontent of the remote catalog based on matching the content items of the local collection and remote catalog. The method includes receiving query input from the user for finding desired content items and determining a subset of content items of the local collection associated with metacontent that at least partially matches the query input in which at least one of the matching metacontents is from the remote catalog. The method also includes presenting the subset of content items based on at least one ranking criterion.

Abstract: A method of and system for enhanced content discovery based on network and device access behavior is disclosed. A method includes providing a remote catalog of global attributes values associated with content items that are based on interactions of a plurality of users with the content items. User interactions with a local device are monitored to determine user preferences and determine local attribute values associated with the content items that are based on interactions of the user with the content items. A subset of content items on the local device is selected based on matching user input with metacontent associate with the content items. The content items of the subset are presented in a ranked order based the user preferences, local attribute values, and the global attribute values.

Abstract: A method of selecting and presenting content based on learned user preferences is provided. The method includes receiving search input from the user for identifying desired content items and receiving content selection actions from the user. The method further includes analyzing the date, day, and time of content selection actions by the user and analyzing descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items. In response to subsequent searches by the user, the method calls for selecting and ordering a collection of content items for presentation to the user based on comparing the user's search input to descriptive terms associated with content items and based on the learned periodicities of the user.

Abstract: A user-interface method of selecting and presenting a collection of content items based on user navigation and selection actions associated with the content is provided. The method includes associating a relevance weight on a per user basis with content items to indicate a relative measure of likelihood that the user desires the content item. The method includes receiving a user's navigation and selections actions for identifying desired content items, and in response, adjusting the associated relevance weight of the selected content item and group of content items containing the selected item. The method includes, in response to subsequent user input, selecting and presenting a subset of content items and content groups to the user ordered by the adjusted associated relevance weights assigned to the content items and content groups.

Abstract: A method of selecting and presenting content on a first system based on user preferences learned on a second system is provided. The method includes receiving a user's input for identifying items of the second content system and, in response thereto, presenting a subset of items of the second content system and receiving the user's selection actions thereof. The method includes analyzing the selected items to learn the user's content preferences for the content of the second content system and determining a relationship between the content of the first and second content systems to determine preferences relevant to items of the first content system. The method includes, in response subsequent user input for items of the first content system, selecting and ordering a collection of items of the first content system based on the user's learned content preferences determined to be relevant to the items of the first content system.

Abstract: A method of selecting and presenting content based on learned user preferences is provided. The method includes receiving search input from the user for identifying desired content items and receiving content selection actions from the user. The method further includes analyzing the date, day, and time of content selection actions by the user and analyzing descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items. In response to subsequent searches by the user, the method calls for selecting and ordering a collection of content items for presentation to the user based on comparing the user's search input to descriptive terms associated with content items and based on the learned periodicities of the user.

Abstract: A user-interface method of selecting and presenting a collection of content items based on user navigation and selection actions associated with the content is provided. The method includes associating a relevance weight on a per user basis with content items to indicate a relative measure of likelihood that the user desires the content item. The method includes receiving a user's navigation and selections actions for identifying desired content items, and in response, adjusting the associated relevance weight of the selected content item and group of content items containing the selected item. The method includes, in response to subsequent user input, selecting and presenting a subset of content items and content groups to the user ordered by the adjusted associated relevance weights assigned to the content items and content groups.

Abstract: A method of selecting and presenting content on a first system based on user preferences learned on a second system is provided. The method includes receiving a user's input for identifying items of the second content system and, in response thereto, presenting a subset of items of the second content system and receiving the user's selection actions thereof. The method includes analyzing the selected items to learn the user's content preferences for the content of the second content system and determining a relationship between the content of the first and second content systems to determine preferences relevant to items of the first content system. The method includes, in response subsequent user input for items of the first content system, selecting and ordering a collection of items of the first content system based on the user's learned content preferences determined to be relevant to the items of the first content system.

Abstract: A method of selecting and presenting content based on learned user preferences is provided. The method includes providing a content system including a set of content items organized by genre characterizing the content items, and wherein the set of content items contains microgenre metadata further characterizing the content items. The method also includes receiving search input from the user for identifying desired content items and, in response, presenting a subset of content items to the user. The method further includes receiving content item selection actions from the user and analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user. The method includes, in response to receiving subsequent user search input, selecting and presenting content items in an order that portrays as relatively more relevant those content items containing microgenre metadata that more closely match the learned microgenre preferences of the user.

Abstract: A method of selecting and presenting content on a first system based on user preferences learned on a second system is provided. The method includes receiving a user's input for identifying items of the second content system and, in response thereto, presenting a subset of items of the second content system and receiving the user's selection actions thereof. The method includes analyzing the selected items to learn the user's content preferences for the content of the second content system and determining a relationship between the content of the first and second content systems to determine preferences relevant to items of the first content system. The method includes, in response subsequent user input for items of the first content system, selecting and ordering a collection of items of the first content system based on the user's learned content preferences determined to be relevant to the items of the first content system.

Abstract: A method of selecting and presenting content based on context-sensitive learned user preferences is provided. The method includes providing a set of content items having descriptive terms. The method includes receiving user input for identifying items and, in response thereto, presenting a subset of items. The method includes receiving user selections of said items and analyzing the descriptive terms of those items to learn the user's content preferences. The method includes determining the context in which the user performed the selections and associating those contexts with the user content preferences learned from the corresponding user selections. The method includes, in response to subsequent user input, determining a context of said subsequent input and selecting and ordering a collection of items based on comparing those items' descriptive terms with the user's learned content preferences associated with the determined context in which the user entered the subsequent input.

Abstract: A method of selecting and presenting content based on learned user preferences is provided. The method includes receiving search input from the user for identifying desired content items and receiving content selection actions from the user. The method further includes analyzing the date, day, and time of content selection actions by the user and analyzing descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items. In response to subsequent searches by the user, the method calls for selecting and ordering a collection of content items for presentation to the user based on comparing the user's search input to descriptive terms associated with content items and based on the learned periodicities of the user.