TY - JOUR
T1 - Design and evaluation of a multi-agent collaborative Web mining system
AU - Chau, Michael
AU - Zeng, Daniel
AU - Chen, Hsinchun
AU - Huang, Michael
AU - Hendriawan, David
N1 - Funding Information:
Fifty undergraduate students, most of them majoring in management information systems, were recruited for the experiment. Six of the 50 topics used in the Sixth Text Retrieval Conference (TREC-6) ad hoc task were selected and modified for use in the context of Web searching [45] . The TREC series was sponsored by the National Institute of Standards and Technology (NIST) and the Defense Advanced Research Projects Agency (DARPA) to encourage research in information retrieval from large text collections. Each subject was given three search topics and asked to perform search and analysis to identify the major themes related to each of them.
Funding Information:
This project was partly supported by the following research grants:
PY - 2003/4
Y1 - 2003/4
N2 - 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.
AB - 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.
KW - Collaboration behavior
KW - Collaborative filtering
KW - Collaborative information retrieval
KW - Multi-agent systems
KW - Post-retrieval analysis
KW - Software agents
KW - Web content mining
KW - Web searching
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U2 - 10.1016/S0167-9236(02)00103-3
DO - 10.1016/S0167-9236(02)00103-3
M3 - Article
AN - SCOPUS:0037375152
SN - 0167-9236
VL - 35
SP - 167
EP - 183
JO - Decision Support Systems
JF - Decision Support Systems
IS - 1
ER -