Abstract: Systems and techniques, including computer program products, for generating sequences of program items. A specification of a sequence is received. A specification of multiple sets, where each set includes one or more program items, is also received. An output sequence of program items is generated by selecting program items from the sets based on the specified sequence. In some implementations, program items are selected by assigning each program item a score, and identifying the program item with the best score. An attribute can be associated with each program item. The attributes can be used to group the program items into sets, to determine the scores of the program items, and to select program items to be placed in the generated output sequence. The rules and the set sequence can be adjusted dynamically, and the generated output sequence can be modified by adding, removing, or replacing program items.

Abstract: Systems and techniques, including computer program products, for generating sequences of program items. A specification of a sequence is received. A specification of multiple sets, where each set includes one or more program items, is also received. An output sequence of program items is generated by selecting program items from the sets based on the specified sequence. In some implementations, program items are selected by assigning each program item a score, and identifying the program item with the best score. An attribute can be associated with each program item. The attributes can be used to group the program items into sets, to determine the scores of the program items, and to select program items to be placed in the generated output sequence. The rules and the set sequence can be adjusted dynamically, and the generated output sequence can be modified by adding, removing, or replacing program items.

Abstract: An online music purchasing system and method is disclosed, in which a radio service operates on a user's computer and is configured for receiving and playing digital radio representations of media content in near real-time in a radio session. A content server is configured for serving the digital radio representations of media content to the radio service, and a radio sequence server is configured for serving a sequential list of currently-playing and previously-played media content of the radio session to the radio service. An account server is configured for receiving a signal indicative of a user's desire to purchase a file of one of a currently-playing or previously-played media content. A download manager is configured for downloading the file to the user's computer according to the signal indicative of the user's desire to purchase the file.

Abstract: A system and a method for managing a database. The system includes a database manager for storing and retrieving data records from a database. In one embodiment, the database includes a database data structure that is divided into a plurality of sections. Each of the sections holds is configured to hold zero or more data records. During a store operation of a data record, a key that is associated with the data record is used to identify one of the sections. The system determines whether the identified section has sufficient space to contain the identified data record. If the section has insufficient space, the system deletes data records according to a ranking function. In one embodiment of the invention, the ranking function is a least recently used algorithm. The system of the present invention does not have any inter-dependency between the data records that are stored within the database.

Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments.

Abstract: An online music purchasing system and method is disclosed, in which a radio service operates on a user's computer and is configured for receiving and playing digital radio representations of media content in near real-time in a radio session. A content server is configured for serving the digital radio representations of media content to the radio service, and a radio sequence server is configured for serving a sequential list of currently-playing and previously-played media content of the radio session to the radio service. An account server is configured for receiving a signal indicative of a user's desire to purchase a file of one of a currently-playing or previously-played media content. A download manager is configured for downloading the file to the user's computer according to the signal indicative of the user's desire to purchase the file.

Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments.

Abstract: Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments, which are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur. Supervised segmentation is applied to merchant vectors to form merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. Consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer.