A Personal TV System receives a plurality of video segments constituting a TV program and information describing each segment, and controls the display of the segments to a viewer in accordance with preferences of the viewer and with the description of each segment. Segments may be omitted or replaced with substitute segments. The viewer may review his preferences and edit or replace them. In a multi-viewer household, the system may prompt a viewer to confirm her preferences. A TV program may contain interactive segments, and when the viewer chooses to interact with a particular segment, the system automatically stores all subsequently received segments for later viewing while the viewer interacts with the selected segment. The system may present TV program choices to the viewer selected and arranged in accordance with her preferences.

System and method for personalized TV

A system and method of the present invention allow users to access, manage, and edit information about content data, often referred to as metadata. Metadata is collected from various sources, added, and maintained in a metadata database. In addition, metadata is dynamically read from the metadata database and dynamically displayed in a graphical user interface in an organized manner, such as a hierarchical tree. In the graphical user interface, a user may add, delete, and/or modify the metadata. As the user changes the metadata, the metadata database is updated and the user's changes are propagated throughout the graphical user interface such that the hierarchical tree is displays the changed metadata.

System and method of managing metadata data

A network-enabled audio device that provides a display device that allows the user to select playlists of music much like a jukebox is disclosed. The user can compose playlists from disk files, CD's, Internet streaming audio broadcasts, online music sites, and other audio sources. The user can also select a desired Web broadcast from a list of available Web broadcasts. In addition, the user can play standard audio CD's and MP3 encoded CD's and have access to local AM/FM stations. Further, the software, the user controls, and the display in the network-enabled audio device are operably configured and connected such that the user can listen to playlists that include CD's and other audio sources just as the user would choose a playlist in a jukebox.

Method and device for obtaining playlist content over a network

The method and system for TV user profile data prediction and modeling allows accurate and narrowly focused behavioral clustering. A client-side system classifies television consumers into representative user profiles. The profiles target individual user advertising and program preference category groups. A contextual behavioral profiling system determines the user's monitor behavior and content preferences, and the system may be continually updated with user information. A behavioral model database is queried by various system modules. The programming, including targeted advertising for television and interactive television is based on the profile data prediction, modeling and preference determination. The system is enabled to present a complete program sequence to the viewer based on the preference determination and stored programming. The latter is referred to as automatic program sequence (virtual channel) creation and the virtual channel can be presented as a separate channel in an electronic programming guide (EPG).

System, method, and software application for targeted advertising via behavioral model clustering, and preference programming based on behavioral model clusters

A system and method for creating a user profile and for using the user profile to order search results returned by a search engine. The user profile is based on search queries submitted by a user, the user's specific interaction with the documents identified by the search engine and personal information provided by the user. Generic scores associated with the search results are modulated by the user profile to measure their relevance to a user's preference and interest. The search results are re-ordered accordingly so that the most relevant results appear on the top of the list. User profiles can be created and/or stored on the client side or server side of a client-server network environment. text analysis.

Personalization of web search

A method for providing automatic, personalized information services to a computer user includes the following steps: transparently monitoring user interactions with data during normal use of the computer; updating user-specific data files including a set of user-related documents; estimating parameters of a learning machine that define a User Model specific to the user, using the user-specific data files; analyzing a document to identify its properties; estimating the probability that the user is interested in the document by applying the document properties to the parameters of the User Model; and providing personalized services based on the estimated probability. Personalized services include personalized searches that return only documents of interest to the user, personalized crawling for maintaining an index of documents of interest to the user; personalized navigation that recommends interesting documents that are hyperlinked to documents currently being viewed; and personalized news, in which a third party server customized its interaction with the user. The User Model includes continually-updated measures of user interest in words or phrases, web sites, topics, products, and product features. The measures are updated based on both positive examples, such as documents the user bookmarks, and negative examples, such as search results that the user does not follow. Users are clustered into groups of similar users by calculating the distance between User Models.

Automatic, personalized online information and product services

Method and system for personalized searching of information and product services by estimating an interest to a user

A method for providing automatic, personalized information services to a computer user includes the following steps: transparently monitoring user interactions with data during normal use of the computer; updating user-specific data files including a set of user-related documents; estimating parameters of a learning machine that define a User Model specific to the user, using the user-specific data files; analyzing a document to identify its properties; estimating the probability that the user is interested in the document by applying the document properties to the parameters of the User Model; and providing personalized services based on the estimated probability. Personalized services include personalized searches that return only documents of interest to the user, personalized crawling for maintaining an index of documents of interest to the user; personalized navigation that recommends interesting documents that are hyperlinked to documents currently being viewed; and personalized news, in which a third party server customized its interaction with the user.

Roy Twersky

Papers

Automatic, personalized online information and product services

Method and system for personalized searching of information and product services by estimating an interest to a user

Methods and systems for conducting a personalized web browser search by probability estimation that is unseen document is of interest to the user