Oracle International Corporation

Oracle Otc Subsidiary LLC

Endeca Technologies, Inc.

Lycos, Inc.

Vladimir V Zelevinsky

Daniel Tunkelang

Joyce Jeanpin Wang

Omri Traub

Joshua William Kapell

Adam J Ferrari

Jason Furtado

Spiro Michaylov

John Huffaker

Matthew L Brandwein

Adam Pocock

Yevgeniy Dashevsky

Vladimir Gluzman Peregrine

Uri Sheffer

Brook Stevens

Mashhood Ishaque

Tristan R Spaulding

Diana Ye

Alexander David Rosen

Frederick C Knabe

Brian Ulicny

Alden Dorosario

Gray Watson

Steven Quince

Stavros Michael MacRakis

Eli Daniel

Gregory C Scott

Eugene Jitomirsky

Ray Kuo

Jonathan Grimm

Herng Albert Sheu

Michael Y Saji

Velin Krassimirov Tzanov

Paul Alexander Wehner

Christopher A Ekberg

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

A system for exploring data receives the data from a database and indexes the data in a server. The system displays one or more selectable datasets from the indexed data, where the selectable datasets include a plurality of attributes. The system receives a selection of one of the plurality of attributes. The system then sorts the one or more attributes by level of interestingness relative to the selected attribute, and displays the sorted attributes.

Guided data exploration

A system for exploring data receives the data from a database and indexes the data in a server. The system displays one or more selectable datasets from the indexed data, where the selected dataset includes one or more attributes. The system then sorts the one or more attributes by level of interestingness and displays the sorted attributes.

A system for performing semantic search receives an electronic text corpus and separates the text corpus into a plurality of sentences. The system parses and converts each sentence into a sentence tree. The system receives a search query and matches the search query with one or more of the sentence trees.

Semantic text search

Information retrieval and navigation using a semantic layer

System and methods for dynamically generating taxonomies of keywords and/or descriptors are provided. In one example, a navigation system for accessing a corpus of information provides for dynamic taxonomy generation expanding upon a topic entered by a user in a user interface. The navigation system generates, dynamically, at least one term associated with the received topic from at least one sense or meaning retrieved from a semantic network. The navigation system is further configured to present to the user the at least one term as a selectable refinement in response to receiving the topic entered by the user in the user interface. The system can also be configured to retrieve terms and/or senses from the semantic network and evaluate any retrieved terms for their informativeness. The system can further cache any information generated during taxonomy creation and update the corpus to reflect useful refinements.

Dynamic creation of topical keyword taxonomies

A data mining system receives a data set that includes a plurality of columns of data. The system determines correlations between columns of data of the data set and displays an interactive listing of a plurality of pairs of columns based on the correlations. The listing includes preview information based on the correlations for each pair. The system receives a selection of a value from the interactive listing from a user and refines the data set in response to the selection.

Interactive data mining

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 measuring the quality of document sets

A system for generating one or more recommended items for a user receives a target items set for the user which includes two or more target items. The system then queries a database of a plurality of related items sets using the target items set, where each related items set comprises a plurality of related items. In response to the querying, the system retrieves one or more similar items sets from the plurality of related item sets, each similar items set being similar to the target items set. The system then performs a union of the similar items sets to generate the recommended items.

Set based item recommendation system

Methods and systems that enable searching with clustering in information access systems are described. The methods of clustering operate on a collection of materials wherein each item in the collection may be associated with one or more properties. An original subset of materials is selected from the collection and relevant properties associated with the subset of materials are clustered into property clusters. Each property cluster generally contains properties that are more similar to each other than to properties in a different property cluster. The property clusters can be used to respond to the query. A mapping function can be used to identify a set of materials that correspond to each property cluster based on the associations between individual items and properties. The property clusters can also be used for iterative query refinement.

Method and system for information retrieval with clustering

Growing community of inventors

Sharon, MA, United States of America

Vladimir V Zelevinsky