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Dynamic selection method of the best search engine for a user's query

Authors:

Kodai Mizuno,

Kyoji KawagoeAuthors Info & Claims

IUCS '09: Proceedings of the 3rd International Universal Communication Symposium

Pages 383 - 388

https://doi.org/10.1145/1667780.1667859

Published: 03 December 2009 Publication History

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Abstract

In this paper, we propose a new dynamic selection method of the best search engine for a user's query. When users retrieve on the Internet, the expert users manually select the best search engine for their queries. However, the most important problem is that the novice users cannot understand features of all search engines. Consequently, because such users cannot select the best search engine, the users cannot obtain the best retrieval results. In this paper, we focus the number of retrieval results, and we calculate search engines' matching scores suitable for the user's query by using this focus point. As a result, novice users can select the best search engine using the scores calculated by our system.

References

[1]

M. Kobayashi and K. Takeda: "Information retrieval on the web", ACM Computing Surveys, 32, 2, pp. 144--173 (2000).

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Google Scholar

[2]

J. Liu, H. Chen, K. Furuse and N. Ohbo: "Supporting web search by using zoomable interface to present relativity", DEWS2008, pp. 1--6 (2008). in Japanese.

Google Scholar

[3]

L. S. Smith and A. R. Hurson: "A search engine selection methodology", ITCC2003, pp. 122--129 (2003).

Digital Library

Google Scholar

[4]

L. Gravano, H. Garcia-Molina and A. Tomasic: "The effectiveness of gloss for the text database discovery problem", ACM SIGMOD Record, 23, pp. 126--137 (1994).

Digital Library

Google Scholar

[5]

L. Gravano, H. Garcia-Molina and A. Tomasic: "Gloss: text-source discovery over the internet", ACM Transactions on Database Systems (TODS), 24, pp. 229--264 (1999).

Digital Library

Google Scholar

[6]

P. G. Ipeirotis, L. Gravano and M. Sahami: "Automatic classification of text databases through query probing", Lecture Notes in Computer Science, 1997/2001, pp. 245--255 (2001).

Digital Library

Google Scholar

[7]

T. Takaki and T. Kitani: "Relevance ranking of documents using query word co-occurrence", Transaction of Information Processing Society of Japan, 40, pp. 74--84 (1999).

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Index Terms

Dynamic selection method of the best search engine for a user's query
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Digital libraries and archives

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Published In

IUCS '09: Proceedings of the 3rd International Universal Communication Symposium

December 2009

404 pages

ISBN:9781605586410

DOI:10.1145/1667780

General Chair:
Kazumasa Enami
National Institute of Information and Communications Technology (NICT), Japan

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 03 December 2009

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IUCS '09: 3rd International Universal Communication Symposium

December 3 - 4, 2009

Tokyo, Japan

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Identifying popular search goals behind search queries to improve web search ranking

A New Algorithm for Inferring User Search Goals with Feedback Sessions

Search Engine Optimization by Re-Ranking the Product Search Result Based on User Click Data

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Identifying popular search goals behind search queries to improve web search ranking

A New Algorithm for Inferring User Search Goals with Feedback Sessions

Search Engine Optimization by Re-Ranking the Product Search Result Based on User Click Data

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