Artificial Intelligence Lab, Department of MIS, University of Arizona / 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 (Alta Vista), thus allowing searches of the significant portion of the 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 (Alta Vista) directly. We also analyzed effects of various related demographic and task related parameters.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/106217 |
Date | January 2001 |
Creators | Roussinov, Dmitri G., Chen, Hsinchun |
Publisher | Elsevier |
Source Sets | University of Arizona |
Language | English |
Detected Language | English |
Type | Journal Article (Paginated) |
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