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Proceedings Paper

Harnessing agent technologies for data mining and knowledge discovery
Author(s): Jenifer S. McCormack; Brian Wohlschlaeger
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Paper Abstract

Data mining and knowledge discovery in databases are providing means to analyze and discover new knowledge from large datasets. The growth of the Internet has provided the average user with the ability to more easily access and gather data. Many of the existing data mining tools require users to have advanced knowledge. New graphical-based tools are needed to allow the average user to easily and quickly discover new patterns and trends from heterogenous data. SAIC is developing an agent-based data mining tool called AgentMinertm as part of an internal research project. AgentMinertm will allow the user to perform advanced information retrieval and data mining to discover patterns and relationships across multiple distributed, heterogeneous data sources. The current system prototype utilizes an ontology to define common concepts and data elements that are contained in the distributed data sources. AgentMinertm can access data from relational databases, structured text, web pages, and open text sources. It is a Java-based application that contains a suite of graphical tools such as the Mission Manager, Graphical Ontology Builder (GOB), and Qualified English Interpreter (QEI). In addition, AgentMinertm provides the capability to support both 2-D and 3-D data visualization, including animation across a selected independent variable.

Paper Details

Date Published: 6 April 2000
PDF: 8 pages
Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381757
Show Author Affiliations
Jenifer S. McCormack, Science Applications International Corp. (United States)
Brian Wohlschlaeger, Science Applications International Corp. (United States)


Published in SPIE Proceedings Vol. 4057:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology II
Belur V. Dasarathy, Editor(s)

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