Oracle International Corporation

Oracle Otc Subsidiary LLC

Omri Traub

Vladimir V Zelevinsky

Adam J Ferrari

Jason Furtado

Joshua William Kapell

Spiro Michaylov

Matthew L Brandwein

John Huffaker

Vladimir Gluzman Peregrine

Daniel Tunkelang

Alexander David Rosen

Joyce Jeanpin Wang

Eli Daniel

Gregory C Scott

Eugene Jitomirsky

Ray Kuo

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

A system for visualizing concepts within a collection of information analyzes a set of materials from at least one collection of information and defines an attribute space associated with the set of materials. The system then determines automatically similarity of members of the attribute space. The system then generates a graphical model of the members of the attribute space, where the generating includes generating a display of the members of the attribute space, each of the members having a respective display distance from other respective members of the attribute space reflective of the determined similarity.

Visualization of concepts within a collection of information

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 concept visualization

Growing community of inventors

Brookline, MA, United States of America

Omri Traub