Stuart J Rose

US Patent:

8352469, Jan 8, 2013

Filed:

Sep 9, 2009

Appl. No.:

12/555962

Inventors:

Stuart J Rose - Richland WA, US

Assignee:

Battelle Memorial Institute - Richland WA

International Classification:

G06F 7/00
G06F 17/30

US Classification:

707736, 707737, 707749, 706 45, 706 46, 706 47

Abstract:

Methods and systems for automatically generating lists of stop words for information retrieval and analysis. Generation of the stop words can include providing a corpus of documents and a plurality of keywords. From the corpus of documents, a term list of all terms is constructed and both a keyword adjacency frequency and a keyword frequency are determined. If a ratio of the keyword adjacency frequency to the keyword frequency for a particular term on the term list is less than a predetermined value, then that term is excluded from the term list. The resulting term list is truncated based on predetermined criteria to form a stop word list.

US Patent:

20030028504, Feb 6, 2003

Filed:

May 8, 2001

Appl. No.:

09/850998

Inventors:

David Burgoon - Columbus OH, US
Steven Rust - Worthington OH, US
Owen Chang - Columbus OH, US
Loraine Sinnott - Columbus OH, US
Stuart Rose - Richland WA, US
Elizabeth Hetzler - Kennewick WA, US
Lucille Nowell - Richland WA, US

International Classification:

G06F007/00

US Classification:

707/001000

Abstract:

A cluster isolation system includes a processor that is operatively coupled to an input device, an output device, and memory. The system determines feature/interval combinations that distinguish one cluster of data objects from other clusters. The processor calculates cluster isolation measurement values at selected cut-off values for each feature. The processor reports the features and feature score intervals that satisfy selected isolation measurement value thresholds.

US Patent:

20080065666, Mar 13, 2008

Filed:

Sep 8, 2006

Appl. No.:

11/517718

Inventors:

Stuart J. Rose - Richland WA, US
Gary R. Danielson - Kennewick WA, US

Assignee:

Battelle Memorial Institute, a part interest - Richland WA

International Classification:

G06F 7/00

US Classification:

707101

Abstract:

Apparatuses, data structures, and computer-implemented methods for mapping relations of items as those items occur in sets, and/or as they are associated with sets, locations and/or attributes are disclosed according to some aspects. In one embodiment, mapping comprises ingesting a corpus of data having one or more initial sets, which comprise one or more initial items, and creating a content map. The content map comprises a mapping of each initial set to one or more content lists wherein entries in a particular content list correspond to initial items in a particular initial set. The mapping of relations can further comprise defining one or more derived sets as combinations, aggregations, or segmentations of one or more of the initial sets and transforming the content map to generate a concordance.

US Patent:

20080082521, Apr 3, 2008

Filed:

Sep 28, 2006

Appl. No.:

11/541173

Inventors:

Gary R. Danielson - Kennewick WA, US
Stuart J. Rose - Richland WA, US

International Classification:

G06F 17/30

US Classification:

707 5

Abstract:

A method and apparatus for analyzing, organizing and manipulating data for use by computer-executable programs by performing the steps of providing a set of documents wherein each document is provided from a document source, mapping the documents to a location in multi-dimensional space wherein each document's position in multidimensional space is determined as a function of the document's relationship to other documents and is expressed as a signature for that document, identifying a unique identifier for each document, providing a graphical representation of the documents, and associating the graphical representation of each document with the document source using the unique identifier so that any manipulation of the graphical representation of the document will result in a corresponding manipulation of the document in at least one computer executable program.

US Patent:

20080306899, Dec 11, 2008

Filed:

Jun 7, 2007

Appl. No.:

11/759803

Inventors:

Michelle L. Gregory - Richland WA, US
Stuart J. Rose - Richland WA, US
Douglas V. Love - West Richland WA, US
Anne Schur - Richland WA, US

International Classification:

G06F 17/30

US Classification:

707 1, 707E17001

Abstract:

Methods, apparatus, and computer-readable media for analyzing conversational-type data by association of two or more types of extracted information in view of time are disclosed according to some aspects. In one embodiment, analysis of conversational-type data comprises identification of topical segments within the conversational-type data and linking of the topical segments with at least one other type of pertinent, extracted information. The linking can be based on a sequential order of utterances that compose, at least in part, the conversational-type data.

US Patent:

20090254581, Oct 8, 2009

Filed:

Apr 4, 2008

Appl. No.:

12/080753

Inventors:

Alan R. Chappell - Seattle WA, US
Christian Posse - Seattle WA, US
Judith R. McCuaig - Guelph, CA
Alan R. Willse - Des Moines IA, US
Alexander A. Donaldson - Seattle WA, US
Stephen C. Tratz - Boise ID, US
David A. Thurman - Kenmore WA, US
Stuart J. Rose - Richland WA, US
Gary R. Danielson - Kennewick WA, US

International Classification:

G06F 7/00
G06F 17/30

US Classification:

707102, 707E17002

Abstract:

An automated method for allowing multiple users to independently analyze a corpus of digital information having discrete elements by providing two or more users access to one or more initial training source of digital information, allowing the users to each define a set of categories, automatically generating a group of digital features associated with at least two of the discrete elements, automatically associating a subset of the discrete elements with at least one of the categories, and automatically determining at least one combination of features and transformed features that identifies at least one of the categories. The automated method allows said two or more users to have the capability to perform the step of defining a set of categories, such that the automated steps of generating a group of digital features, associating a subset of said discrete elements, and determining at least one combination of features and transformed features is in whole or in part determined by the manual input to the automated method.

US Patent:

20110004465, Jan 6, 2011

Filed:

Sep 28, 2009

Appl. No.:

12/568365

Inventors:

Stuart J. Rose - Richland WA, US
Wendy E. Cowley - Richland WA, US
Vernon L. Crow - Richland WA, US

Assignee:

BATTELLE MEMORIAL INSTITUTE - Richland WA

International Classification:

G06F 17/27

US Classification:

704 9

Abstract:

Systems and computer-implemented processes for computation and analysis of significant themes in a corpus of documents. The computation and analysis of significant themes can be executed on a processor and involves generating a lexical unit document association (LUDA) vector for each lexical unit that has been provided and quantifying similarities between each unique pair of lexical units. The LUDA vector characterizes a measure of association between its corresponding lexical unit and documents in the corpus. The lexical units can then be grouped into clusters such that each cluster contains a set of lexical units that are most similar as determined by the LUDA vectors and a predetermined clustering threshold.

US Patent:

20110060747, Mar 10, 2011

Filed:

Sep 9, 2009

Appl. No.:

12/555916

Inventors:

Stuart J. Rose - Richland WA, US
Wendy E. Cowley - Richland WA, US
Vernon L. Crow - Richland WA, US
Nicholas O. Cramer - Richland WA, US

Assignee:

BATTELLE MEMORIAL INSTITUTE - Richland WA

International Classification:

G06F 17/30

US Classification:

707750, 707E17014, 707E17008

Abstract:

Methods and systems for rapid automatic keyword extraction for information retrieval and analysis. Embodiments can include parsing words in an individual document by delimiters, stop words, or both in order to identify candidate keywords. Word scores for each word within the candidate keywords are then calculated based on a function of co-occurrence degree, co-occurrence frequency, or both. Based on a function of the word scores for words within the candidate keyword, a keyword score is calculated for each of the candidate keywords. A portion of the candidate keywords are then extracted as keywords based, at least in part, on the candidate keywords having the highest keyword scores.