Abstract: A recommendation system and method are disclosed. In the system and method, the personal schedule of the user is used to modify the recommendation functions of media events. The personal schedule may be entered by the user or determined through monitoring over time. An exemplary recommendation function modification is if a media event ends after the user's bedtime, as indicated by the personal schedule. In this example, the recommendation function of that event will be reduced in value because the user will likely go to bed before the event is over.

Abstract: Different images, or sub-images, are rendered at different wavelet decoding rates, the more rapidly decoded wavelets forming a focal region about which less detailed images, or sub-images, are formed. In a preferred embodiment, sets of images or sub-images form levels of a hierarchy, and the wavelet encodings of these images and sub-images are decoded at rates associated with each level of the hierarchy. A single image may be partitioned into sub-images, or regions, that form each level of the hierarchy, or independent images may be arranged in a hierarchical manner, and subsequently rendered using a hierarchy of wavelet decoding schemes. The hierarchy can be developed at a remote site, and a hierarchical wavelet encoding can be transmitted to a local site, so that the hierarchical foveation effect can be rendered while the details of the lower levels of the hierarchy are being communicated.

Abstract: A system employing an automated collaborative filtering process for recommending an item to a viewer based upon feedback data, implicit data, and/or explicit data corresponding to a primary viewer as well as secondary viewers is disclosed. A first act of the automated collaborative filtering process is to match data indicative of a viewing of a first group of items by the primary viewer to data indicative of a viewing of a second group of items by the secondary viewers. A second act of the automated collaborative filtering process is to generate a recommendation of the item by the primary viewer as a function of data indicative of one or more attributes of the item as compared to the data matching accomplished in the first act.

Abstract: Disclosed is a method and system for switching a commercial for a user. Accordingly, the present invention obtains a user's profile or monitors a user's viewing history of various commercials to determine the type of commercials that are not watched or not liked by the user. Thereafter, commercials between television programs are detected during a commercial break and compared with the user's profile or the user's past viewing information to determine whether the detected commercial is liked by the user.

Abstract: A program recommendation system employing a program record module and one of various nearest neighbor modules is disclosed. In response to a reception of a program record, the program record module converts each key field of the program record into a feature value. A single neighbor module selectively generates a recommendation of a program corresponding to the program record based upon a stored program record qualifying as a nearest neighbor of the received program record. A multiple neighbor module selectively generates a recommendation of the program corresponding to the program record based upon N number of stored program records qualifying as N number of nearest neighbors of the received program record. A neighbor cluster selectively generates a recommendation of the program corresponding to the program record based upon the cluster of stored program records qualifying as the nearest neighbor of the received program record.

Abstract: A user interface for querying and displaying records from a database employs a physical metaphor for the process of constructing queries and viewing results. The criteria are represented in displays as symbols that can be included in a query. The display of the symbols are ranked in terms of their respective utility, where the utility is inferred from the commands received to generate the queries. In one embodiment, the ranking is based on frequency of use. The ranking may be indicated by various display effects. For example, in an embodiment, the search criteria are indicated as strings of beads in a three-dimensional scene, each bead representing a criterion and each string representing a different category. For example the criteria, drama, action, suspense, and horror may be included in a category of genre. Criteria are selected to form a query by moving corresponding beads to a query string which is then submitted to perform the search.

Abstract: A system, method, and article of manufacture is disclosed suitable for displaying selectable time orderable options, such as television programs available for viewing on a television, using a tunnel interface. The tunnel interface displays concentric rings where each ring represents a different set of option data whose attributes are modified to reflect a user's preferences. The modified option data are further arranged such that each concentric ring is ordered by time. Additionally, choices within each ring are visually distinguishable by user preference. Users can navigate within and between the concentric rings and select one or more of the available options using the concentric rings.

Abstract: A program recommendation system employing a plurality of classifier modules is disclosed. In response to a reception of a record corresponding to a program, a classifier module correlated to a programming category indicated by the record as corresponding to the program will generate a recommendation of the program or each classifier module generates a recommendation of the program when the record fails to indicate a programming category corresponding to the program. When multiple recommendations are generated, a program record module of the system ranks the recommendations and utilizes the highest rank recommendation for the program.

Abstract: A system, method, and article of manufacture suitable for automatically generating recommendations of a set of entertainment options from a larger set of entertainment options based on user preferences for those options. In particular, the present invention relates to the field of automatically generating recommendations for viewing television programs based on past viewing patterns and preferences of a plurality of television viewers, all of whom do not need to be physically present in front of the television. The present invention creates a composite user profile based on individual profiles for each user detected who is to be used in the composite user profile, some of whom need not be present in front of the television. Each user's preferences may be weighted the same as each other user's or users may have differing weights assigned to their preferences.

Abstract: A system and method for filtering selections and presenting recommendations. A filter that is associated with a media system receives data comprising one or more personal characteristics of a user of the media system. The filter determines at least one recommendation for the user of a selection available on the media system based upon at least one of the personal characteristics of the user.

Abstract: Information nodes are dynamically organized and information related to each node is displayed in dependence upon a user's indicated reference node. The information related to the reference node is displayed prominently, and information items related to the other nodes are displayed with a prominence that reflects each node's degree of separation from the user selected reference node. Both size and position are used to indicate prominence. To present a consistent interface regardless of the user's point of reference, recursive techniques, such as fractal based algorithms, are used in a preferred embodiment.

Abstract: Methods and apparatuses for recommending television programs are provided. The methods provided include obtaining a list of one or more television programs to at least three different program recommenders, obtaining from each recommender a recommendation score, and computing a combined recommendation score by applying a voting process. The combined recommendation score is then presented to a user, who, based thereon, can select a television program of interest. The voting process is a stochastic method including a Bayesian method, a hierarchical decision tree, a memory based learning process, a rule based learning process, a neural network or a hidden markov model. The enumerated stochastic processes can be further combined according to a combination scheme including a unison scheme, a majority scheme, a trust scheme, an averaging scheme or mixture thereof.

Abstract: A method for learning a concept description from an example set containing a plurality of positive and/or negative examples. The method including the steps of: initializing a general set to contain a null concept description; initializing a specific set to contain a concept description of a first positive example from the example set; and making the specific set more general according to each additional positive example from the example set and making the general set more specific according to each additional negative example from the example set until the specific and general sets converge to a single concept description. Preferably, the plurality of positive and negative examples contain description regarding television programming of a viewer and the concept description indicates a type of television programming the viewer likes.

Abstract: A system having a video display screen that provides video to a user. The position of the display screen is adjustable based upon the location of the user with respect to the display screen. The system includes at least one image capturing device trainable on a viewing region of the display screen and coupled to a control unit having image recognition software. The image recognition software identifies the user in an image generated by the image capturing device. The software of the control unit also generates at least one measurement of the position of the user based upon the detection of the user in the image.

Abstract: A television program selection system and method that utilize key frame images of each program. The key frame images are extracted from the recorded show as the program progresses. This continuum of key frame images provides the viewer with a condensed story line and scope of each program, thus allowing the viewer to make an intelligent choice of the programs that he or she intends to record and/or watch.

Abstract: A system for providing an interactive interface, wherein a television viewer can create a personal television channel. Such a system has the advantage of eliminating the need to peruse or surf television guides for the programs that an individual television viewer wants to watch. The personal channel contains all of the preferential programs selectable by the television viewer.

Abstract: A dynamic method and system for processing video source frames (e.g., a television movie) with a video processing system (VPS) that includes a processor, a memory structure, input devices, and an output display. The video source frames, which are received by the VPS from a video source, are executed by the processor. While the video source frames are being executed, a subset of the frames, called key frames, are extracted from the video source frames and stored in the memory structure. The extracting of the key frames is implemented in accordance with a frame extraction algorithm. The extracting is terminated prior to completion of execution of the video source frames. Following termination of extracting, the key frames are reviewed by a user with the output display to determine whether to watch the remainder of the video source frames. The key frames are erased after being reviewed.

Abstract: Real-time events are electronically recommended using a fuzzy-now function of time. Real-time experiencing apparatus can be automatically tuned to a particular real-time event using a surf ring related to recommendations or automatically without a user request.

Abstract: A television programming recommender is disclosed that selectively obtains feedback information from a user to update one or more profiles associated with the user. Previously obtained implicit and explicit preferences are utilized to selectively focus the collection of feedback information to further update and refine the implicit and explicit preferences. The present invention obtains feedback from a user in a manner that maximizes the value of the obtained information and improves the performance of the television programming recommender. The present invention automatically requests feedback from the user upon the occurrence of predefined criteria. The nature of the requested feedback, and the manner in which the obtained feedback is used to adjust a profile, can vary.

Abstract: A user interface for a TV recommender system includes a display screen having a first region for displaying a rating derived from a previously defined TV viewing preference profile contained in the recommender system; and a second region displaying preference settings in the profile which were used to derive the rating. The user interface enables the preference settings to be changed if the rating derived by the profile is incorrect. Additionally, the user interface allows for new features to be added to the profile, which were not previously a part of the profile. Further, a method for correcting a previously defined TV viewing preference profile used in a TV recommender system to more accurately reflect a user's preferences.