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Discovering the representative of a search engine
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Source Conference on Information and Knowledge Management archive
Proceedings of the tenth international conference on Information and knowledge management table of contents
Atlanta, Georgia, USA
Poster Session: Information Retrieval and Text Mining table of contents
Pages: 577 - 579  
Year of Publication: 2001
ISBN:1-58113-436-3
Authors
King-Lup Liu  DePaul University, Chicago, IL
Adrain Santoso  DePaul University, Chicago, IL
Clement Yu  University of Illinois at Chicago, Chicago, IL
Weiyi Meng  SUNY-Binghamton, Binghamton, NY
Sponsors
SIGMIS: ACM Special Interest Group on Management Information Systems
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 34,   Citation Count: 8
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ABSTRACT

Given a large number of search engines on the Internet, it is difficult for a person to determine which search engines could serve his/her information needs. A common solution is to construct a metasearch engine on top of the search engines. Upon receiving a user query, the metasearch engine sends it to those underlying search engines which are likely to return the desired documents for the query. The selection algorithm used by a metasearch engine to determine whether a search engine should be sent the query typically makes the decision based on the search-engine representative, which contains characteristic information about the database of a search engine. However, an underlying search engine may not be willing to provide the needed information to the metasearch engine. This paper shows that the needed information can be estimated from an uncooperative search engine with good accuracy. Two pieces of information which permit accurate search engine selection are the number of documents indexed by the search engine and the maximum weight of each term. In this paper, we present techniques for the estimation of these two pieces of information.


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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W. Meng, K. Liu, C. Yu, W. Wu, and N. Rishe. Estimating the usefulness of search engines. In ICDE, March 1999.
 
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CITED BY  8

Collaborative Colleagues:
King-Lup Liu: colleagues
Adrain Santoso: colleagues
Clement Yu: colleagues
Weiyi Meng: colleagues