Oracle International Corporation

Endeca Technologies, Inc.

Joshua William Kapell

Vladimir V Zelevinsky

Adam J Ferrari

Jason Furtado

Omri Traub

Spiro Michaylov

Matthew L Brandwein

John Huffaker

Daniel Tunkelang

Alexander David Rosen

Joyce Jeanpin Wang

Eugene Jitomirsky

Paul Alexander Wehner

Herng Albert Sheu

Gregory C Scott

Eli Daniel

Vladimir Zelevinsky

Systems and methods for information retrieval are provided that permit users and/or processing entities to access and define synthetic data, synthetic objects, and/or synthetic groupings of data in one or more collections of information. In one embodiment, data access on an information retrieval system can occur through an interpretation layer which interprets any synthetic data against data physically stored in the collection. Synthetic data can define virtual data objects, virtual data elements, virtual data attributes, virtual data groupings, and/or data entities that can be interpreted against data that may be stored physically in the collection of information. The system and methods for information retrieval can return results from the one or more collections of information based not only on the data stored, but also on the virtual data generated from interpretation of the stored data.

Information retrieval and navigation using a semantic layer and dynamic objects

Information retrieval and navigation using a semantic layer

Systems and methods are described that calculate the interestingness of a set of one or more records in a database, either absolutely (i.e., compared to an overall collection of records) or relative to some other set of records. In one embodiment, the measure is a relative entropy value that has been normalized. Various applications of the measure are described in the context of an information retrieval system. These applications include, for example, guiding query interpretation, guiding view selection and summarization, intelligent ranges, event detection, concept triggers and interpreting user actions, hierarchy discovery, and adaptive data mining.

System and method for measuring the quality of document sets

Growing community of inventors

Brooklyn, NY, United States of America

Joshua William Kapell