Abstract: A data processing system generates recommendations for on-line shopping by scoring recommendations matching the customer's cart contents product page, configuration page, email and/or history using predetermined scoring criteria, such as item availability, item price, relevance of the item to the customer, item clarity, item exposure, total purchase amount in the cart, margin, recommendation confidence and lift, shopper profile matches, seasonality, customer history, time dependency, product marketing emphasis, substitutability, item popularity and/or product attributes associated with the recommended item. The scored recommendations may be ranked and/or filtered to prioritize the recommendations so that the best recommendation is selected for presentation to the customer. In addition, one or more scoring criteria or product attributes for the recommended item may be used to select a specific selling point/message text for inclusion with the selected recommendation.

Abstract: A data processing system processes data sets (such as low-resolution transaction data) into high-resolution data sets by mapping generic information into attribute-based specific information that is stored in a database. The extracting frequent pattern information from the database using frequent pattern growth techniques, a compact frequent pattern tree data structure efficiently holds frequent pattern information for multiple transactions having one or more items in each transaction. Frequent pattern data is transformed for ease of use with rule generation algorithms by removing redundant information (such as part group items) or by consolidating items corresponding to a part group and replacing those items with a proxy item for purposes of power set generation.

Abstract: In a particular embodiment, configuration patterns are used to provide solutions to configuration problems that repetitively occur. Use of configuration patterns in connection with a configuration model has many benefits. A configuration pattern is a parameterized or otherwise easily extensible solution to that problem, such that the solution is reusable by modifying the parameters of the pattern or extending the pattern in pre-defined ways. Configuration patterns are inherently data-driven and provide improved maintenance for data and logic as well as reduced programming effort. Configuration patterns can be reused within and across different product families and can be specialized from other patterns. Thus, the use of configuration patterns facilitates reduced maintenance cost and reduced programming effort for product configuration data and logic systems.