Harnessing agent technologies for data mining and knowledge discovery


Data mining and knowledge discovery in databases are providing a 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 heterogeneous data. SAIC is developing an agent-based data mining tool called AgentMinerm as part of an internal research project. AgentMiner 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. AgentMiner 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, AgentMiner provides the capability to support both 2-D and 3-D data visualization, including animation across a selected independent variable.

DOI: 10.1117/12.381757

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@inproceedings{McCormack2000HarnessingAT, title={Harnessing agent technologies for data mining and knowledge discovery}, author={Jenifer S. McCormack and Brian Wohlschlaeger}, booktitle={Data Mining and Knowledge Discovery: Theory, Tools, and Technology}, year={2000} }