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Personalized spiders for web search and analysis
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Source International Conference on Digital Libraries archive
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries table of contents
Roanoke, Virginia, United States
Pages: 79 - 87  
Year of Publication: 2001
ISBN:1-58113-345-6
Authors
Michael Chau  Dept of Management Info. Sys., The University of Arizona, Tucson, Arizona
Daniel Zeng  Dept of Management Info. Sys., The University of Arizona, Tucson, Arizona
Hinchun Chen  Dept of Management Info. Sys., The University of Arizona, Tucson, Arizona
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 103,   Citation Count: 12
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ABSTRACT

Searching for useful information on the World Wide Web has become incr easingly difficult. While Internet search engines have been helping people to search on the web, low recall rate and outdated indexes have become more and more problematic as the web grows. In addition, search tools usually present to the user only a list of search results, failing to provide further personalized analysis which could help users identify useful information and comprehend these results. To alleviate these problems, we propose a client-based architecture that incorporates noun phrasing and self-organizing map techniques. Two systems, namely CI Spider and Meta Spider, have been built based on this architecture. User evaluation studies have been conducted and the findings suggest that the proposed architecture can effectively facilitate web search and analysis.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Lawrence, S. and Giles, C. L. Accessibility of Information on the Web, Nature, 400 (1999), 107-109.
 
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Lin, C., Chen, H. and Nunamaker J. Verifying the Proximity and Size Hypothesis for Self-Organizing Maps. Journal of Management Information Systems, 16(3) (1999- 2000), 61-73.
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Selberg, E. and Etzioni, O. The MetaCrawler architecture for resource aggregation on the Web. IEEE Expert (1997).
 
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CITED BY  12

Collaborative Colleagues:
Michael Chau: colleagues
Daniel Zeng: colleagues
Hinchun Chen: colleagues