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Decision Support Systems
Volume 35, Issue 1, April 2003, Pages 167-183
 
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doi:10.1016/S0167-9236(02)00103-3    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2002 Elsevier Science B.V. All rights reserved.

Design and evaluation of a multi-agent collaborative Web mining system

Michael ChauCorresponding Author Contact Information, E-mail The Corresponding Author, Daniel ZengE-mail The Corresponding Author, Hsinchun ChenE-mail The Corresponding Author, Michael HuangE-mail The Corresponding Author and David HendriawanE-mail The Corresponding Author

Department of Management Information Systems, Eller College of Business and Public Administration, The University of Arizona, Tucson, AZ 85721, USA

Available online 4 June 2002.

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Abstract

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 subjects' 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 users' 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.

Author Keywords: Web searching; Web content mining; Collaborative information retrieval; Collaboration behavior; Collaborative filtering; Multi-agent systems; Software agents; Post-retrieval analysis

Article Outline

1. Introduction
2. Related work
2.1. Web search engines
2.2. Web content mining and post-retrieval analysis
2.3. Collaborative information retrieval and collaborative filtering
2.4. Software agents
2.4.1. Agents on the Web
2.4.2. Multi-agent systems
2.5. Problems in current approaches
3. Collaborative spider: system architecture and main components
3.1. User agent
3.2. Scheduler agent
3.3. Collaborator agent
3.4. Data repository design
3.5. Agent communication language
4. Sample user sessions using Collaborative Spider
4.1. User registration
4.2. Web search and analysis
4.3. Accessing other users' search sessions
4.4. Saving and sharing search sessions
4.5. Monitoring sessions
5. Evaluation methodology
5.1. Experimental design
5.2. Performance measures
6. Experimental results and discussions
6.1. Quantitative results
6.2. Collaboration behavior
7. Conclusion and future directions
Acknowledgements
References
Vitae








Decision Support Systems
Volume 35, Issue 1, April 2003, Pages 167-183
 
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