Intelligent Metasearch Engine for Knowledge Management

Eui-Hong (Sam) Han, George Karypis, Doug Mewhort, and Keith Hatchard
12th Conference of Information and Knowledge Management, pp. 492-495, 2003
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Abstract
The explosive growth of available information sources and the resulting information overload pose several problems for users in many business organizations and educational institutions. First, searching through several information sources, one at a time, is a source of enormous frustration for users. Second, top-ranked documents in search results are frequently irrelevant to what users are interested in. To address these problems, we have developed ixmetaâ„¢, a powerful metasearch engine that gathers, evaluates, ranks, and reports the most relevant results from multiple information sources, including library catalogs, proprietary databases, intranets, and Web search engines. In addition to basic metasearch capabilities, ixmetafind uses personalization and clustering techniques to find the most relevant results for users. In this paper, we briefly describe technologies used in ixmetafind and present pinpointâ„¢ from Sagebrush Corporation, the smart research toolâ„¢ in the kindergarten through twelfth grade (K-12) school environment. Pinpoint showcases ixmetafind in the knowledge management domain of the K-12 school environment.
Research topics: Clustering | Data mining | Information retrieval