Battelle Memorial Institute

Battelle Memorial Research

Augustin J Calapristi

Nancy E Miller

Vernon L Crow

Jeffrey D Saffer

Randall E Scarberry

Heidi Sofia

Guang Chen

Lisa C Stillwell

Elizabeth G Hetzler

Alan E Turner

Deborah A Payne

Sean J Zabriskie

Antonio P Sanfilippo

Susan L Havre

Lucille T Nowell

Scott D Decker

Philip J Monroe

Sarah J Thurston

Cory L Albright

Kevin M Groch

Joel M Malard

Gregory S Thomas

Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

A system or method consistent with an embodiment of the present invention is useful in analyzing large volumes of different types of data, such as textual data, numeric data, categorical data, or sequential string data, for use in identifying relationships among the data types or different operations that have been performed on the data. A system or method consistent with the present invention determines and displays the relative content and context of related information and is operative to aid in identifying relationships among disparate data types. Various data types, such as numerical data, protein and DNA sequence data, categorical information, and textual information, such as annotations associated with the numerical data or research papers may be correlated for visual analysis. A variety of user-selectable views may be correlated for user interaction to identify relationships that exist among the different types of data or various operations performed on the data. Furthermore, the user may explore the information contained in sets of records and their associated attributes through the use of interactive 2-D line charts and interactive summary miniplots.

Data processing, analysis, and visualization system for use with disparate data types

Systems and methods provide several enhancements for the viewing, analysis, and generation of landscape views in a data analysis system, including: allowing a user to select from multiple methods to generate a landscape view, providing labels for peaks of a landscape, enabling the user to replace labels displayed on the landscape view, enabling a landscape view to be recalculated based on the replacement labels, and allowing a user to switch or morph between two landscape views generated by different methods. Such methods or systems generate graphical landscape map visualizations from a set of data records.

Systems and methods for improving concept landscape visualizations as a data analysis tool

Systems for creating high-dimensional vectors representing sequence strings and biopolymer materials are provided. A first system for divides respective sequence strings into blocks of at least three units to create a vocabulary of blocks. A second system selects predefined domains of a plurality of items of biopolymer materials. A third system defines each item of biopolymer material in a data set of biopolymer materials as a surface using descriptors of at least one of structure and function. A fourth system compares information regarding each biopolymer material of a plurality of biopolymer materials to information regarding each other biopolymer material.

Method and apparatus for extracting attributes from sequence strings and biopolymer material

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West Richland, WA, United States of America

Augustin J Calapristi