Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
C4.5: programs for machine learning
C4.5: programs for machine learning
Experiences with selecting search engines using metasearch
ACM Transactions on Information Systems (TOIS)
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Inquirus, the NECI meta search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Document Categorization and Query Generation on the World Wide WebUsing WebACE
Artificial Intelligence Review - Special issue on data mining on the Internet
Expert agreement and content based reranking in a meta search environment using Mearf
Proceedings of the 11th international conference on World Wide Web
Fusion Via a Linear Combination of Scores
Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Foundations and Trends in Information Retrieval
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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 ixmeta™, 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 pinpoint™ from Sagebrush Corporation, the smart research tool™ in the kindergarten through twelfth grade (K-12) school environment. Pinpoint showcases ixmetafind in the knowledge management domain of the K-12 school environment.