Information navigation on the web by clustering and summarizing query results |
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| Authors: | Dmitri G. Roussinov Hsinchun Chen |
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| Affiliation: | a School of Information Studies, Syracuse University, 4-234 Center for Science and Technology, Syracuse, NY 13244-4100, USA;b Department of MIS, College of BPA, University of Arizona, Tucson, AZ 85721, USA |
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| Abstract: | We report our experience with a novel approach to interactive information seeking that is grounded in the idea of summarizing query results through automated document clustering. We went through a complete system development and evaluation cycle: designing the algorithms and interface for our prototype, implementing them and testing with human users. Our prototype acted as an intermediate layer between the user and a commercial Internet search engine (AltaVista), thus allowing searches of the significant portion of World Wide Web. In our final evaluation, we processed data from 36 users and concluded that our prototype improved search performance over using the same search engine (AltaVista) directly. We also analyzed effects of various related demographic and task related parameters. |
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| Keywords: | Information retrieval Neural networks Clustering Summarization Relevance feedback World Wide Web Internet spiders Search engines |
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