Abstract: Systems and methods for delivering personalized content streams over a variety of devices and networks are disclosed. A user's preferences, customizations, and content are made available to the user through specialized clients for home, car, office, and portable environments. In order to enable personalized content streams on devices that are intermittently connected or that make use of network bandwidth during off-peak hours, the system prescribes a distributed content sequencing engine and a distributed, synchronized user profile and station/channel definitions. The system is also designed to support players connected via unidirectional or asymmetric connections such as satellite radios with or without an upstream data link.

Abstract: Systems and methods are disclosed for providing devices capable of the reception and playback of one or more crafted media channels transmitted over an intermittent connection. The one or more channels may be customized by the end user to bias the programming towards individual tastes or moods. The channels may be delivered over an intermittent, unidirectional link, for example a Satellite Radio receiver in a home or car. Content may also be delivered over an intermittent, bidirectional link, for example to a portable media player via a wireless 802.11 or other networked connection.

Abstract: A system, method, and machine-readable medium are disclosed for the controlled, non-real-time conveyance of digital content for playback. Digital content and associated metadata are marked, rated, categorized, and then converted into encoded digital data. The resulting encoded digital data is transmitted as a plurality of data streams through a communications facility such as a satellite, wireless, or physical network. The data streams are received by a content receiver where they are decoded into metadata and digital content for controlled conveyance and playback. A digital content management module comprising a content selection algorithm compares metadata associated with candidate digital content to a predetermined content selection profile. If the metadata matches predetermined selection parameters of the selection profile, the candidate digital content and its associated metadata are stored in a machine-readable medium for controlled conveyance and playback.

Abstract: Systems and methods are disclosed for providing devices capable of the reception and playback of one or more crafted media channels transmitted over an intermittent connection. The one or more channels may be customized by the end user to bias the programming towards individual tastes or moods. The channels may be delivered over an intermittent, unidirectional link, for example a Satellite Radio receiver in a home or car. Content may also be delivered over an intermittent, bidirectional link, for example to a portable media player via a wireless 802.11 or other networked connection.

Abstract: A method and apparatus for receiving and selectively storing digital content broadcasted through a communication channel via any transmission means, while interacting with said digital content in a content receiver unit. Digital content and associated metadata are received, associated metadata is analyzed, and then both are selectively stored based on such analysis. In one embodiment, current digital content is received and stored by the content receiver unit, while the oldest digital content is discarded, in a first in-first out (FIFO) fashion. In another embodiment, current digital content is received by a content receiver unit, metadata is analyzed in regards to content selection criteria in addition to available memory, and digital content and associated metadata is selectively stored based on such analysis. In still another embodiment of the present invention, metadata associated with selectively stored digital content is analyzed further for selective playback of said digital content.

Abstract: A system, method, and computer program product perform text equivalencing. The text equivalencing is performed by modifying a string of characters by applying a set of heuristics, comparing the modified strings of characters to known strings of characters. If a match is found, the text equivalencing engine performs database update and exits. If no match is found, sub-strings are formed by grouping together frequently occurring sets of characters. An information retrieval technique is performed on the sub-strings to determine equivalent text.

Abstract: A system, method, and computer program product discover relationships among items and recommend items based on the discovered relationships. The recommendations provided by the present invention are based on user profiles that take into account actual preferences of users, without requiring users to complete questionnaires. An improved binomial log likelihood ratio analysis technique is applied, to reduce adverse effects of overstatement of coincidence and predominance of best sellers. The invention may be used, for example, to generate track lists for a personalized radio station.

Abstract: A system, method, and computer program product discover relationships among items and recommend items based on the discovered relationships. The recommendations provided by the present invention are based on user profiles that take into account actual preferences of users, without requiring users to complete questionnaires. An improved binomial log likelihood ratio analysis technique is applied, to reduce adverse effects of overstatement of coincidence and predominance of best sellers. The invention may be used, for example, to generate track lists for a personalized radio station.

Abstract: A system and method for selecting and presenting personally targeted entities such as advertising, coupons, products and information content, based on tracking observed behavior on a user-by-user basis and utilizing an adaptive vector space representation for both information and behavior. The system matches users to entities in a manner that improves with increased operation and observation of user behavior. User behavior and entities (ads, coupons, products) and information (text) are all represented as content vectors in a unified vector space. The system is based on an information representation called content vectors that utilizes a constrained self organization learning technique to learn the relationships between symbols (typically words in unstructured text). Users and entities are each represented as content vectors.