Artificial Intelligence Lab, Department of MIS, University of Arizona / Most existing Web search tools work only with individual users and do not help a user benefit from previous search
experiences of others. In this paper, we present the Collaborative Spider, a multi-agent system designed to provide post-retrieval
analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions
and share them with other users. We also report a user study designed to evaluate the effectiveness of this system. Our
experimental findings show that subjectsâ search performance was degraded, compared to individual search scenarios in which
users had no access to previous searches, when they had access to a limited number (e.g., 1 or 2) of earlier search sessions done
by other users. However, search performance improved significantly when subjects had access to more search sessions. This
indicates that gain from collaboration through collaborative Web searching and analysis does not outweigh the overhead of
browsing and comprehending other usersâ past searches until a certain number of shared sessions have been reached. In this
paper, we also catalog and analyze several different types of user collaboration behavior observed in the context of Web mining.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105861 |
| Date | 04 1900 |
| Creators | Chau, Michael, Zeng, Daniel, Chen, Hsinchun, Huang, Michael, Hendriawan, David |
| Publisher | Elsevier |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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