Database selection and result merging in P2P web search

S. Chernov, Pavel Serdyukov, M. Bender, S. Michel, G. Weikum, C. Zimmer

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Intelligent Web search engines are extremely popular now. Currently, only the commercial centralized search engines like Google can process terabytes of Web data. Alternative search engines fulfilling collaborative Web search on a voluntary basis are usually based on a blooming Peer-to-Peer (P2P) technology. In this paper, we investigate the effectiveness of different database selection and result merging methods in the scope of P2P Web search engine Minerva. We adapt existing measures for database selection and results merging, all directly derived from popular document ranking measures, to address the specific issues of P2P Web search. We propose the general approach to both tasks based on the combination of pseudo-relevance feedback methods. From experiments with TREC Web data, we observe that the pseudo-relevance feedback information from the topically organized collections improves retrieval quality.
Original languageUndefined
Title of host publicationProceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005)
Place of PublicationHeidelberg, Germany
PublisherSpringer
Pages26-37
Number of pages12
ISBN (Print)978-3-540-71660-0
DOIs
Publication statusPublished - Sep 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume4125

Keywords

  • DB-CAQ: CONTEXT-AWARE QUERYING
  • EWI-7412
  • IR-63552
  • METIS-227478

Cite this

Chernov, S., Serdyukov, P., Bender, M., Michel, S., Weikum, G., & Zimmer, C. (2005). Database selection and result merging in P2P web search. In Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005) (pp. 26-37). [10.1007/978-3-540-71661-7_3] (Lecture Notes in Computer Science; Vol. 4125). Heidelberg, Germany: Springer. https://doi.org/10.1007/978-3-540-71661-7_3
Chernov, S. ; Serdyukov, Pavel ; Bender, M. ; Michel, S. ; Weikum, G. ; Zimmer, C. / Database selection and result merging in P2P web search. Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005). Heidelberg, Germany : Springer, 2005. pp. 26-37 (Lecture Notes in Computer Science).
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abstract = "Intelligent Web search engines are extremely popular now. Currently, only the commercial centralized search engines like Google can process terabytes of Web data. Alternative search engines fulfilling collaborative Web search on a voluntary basis are usually based on a blooming Peer-to-Peer (P2P) technology. In this paper, we investigate the effectiveness of different database selection and result merging methods in the scope of P2P Web search engine Minerva. We adapt existing measures for database selection and results merging, all directly derived from popular document ranking measures, to address the specific issues of P2P Web search. We propose the general approach to both tasks based on the combination of pseudo-relevance feedback methods. From experiments with TREC Web data, we observe that the pseudo-relevance feedback information from the topically organized collections improves retrieval quality.",
keywords = "DB-CAQ: CONTEXT-AWARE QUERYING, EWI-7412, IR-63552, METIS-227478",
author = "S. Chernov and Pavel Serdyukov and M. Bender and S. Michel and G. Weikum and C. Zimmer",
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Chernov, S, Serdyukov, P, Bender, M, Michel, S, Weikum, G & Zimmer, C 2005, Database selection and result merging in P2P web search. in Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005)., 10.1007/978-3-540-71661-7_3, Lecture Notes in Computer Science, vol. 4125, Springer, Heidelberg, Germany, pp. 26-37. https://doi.org/10.1007/978-3-540-71661-7_3

Database selection and result merging in P2P web search. / Chernov, S.; Serdyukov, Pavel; Bender, M.; Michel, S.; Weikum, G.; Zimmer, C.

Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005). Heidelberg, Germany : Springer, 2005. p. 26-37 10.1007/978-3-540-71661-7_3 (Lecture Notes in Computer Science; Vol. 4125).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Database selection and result merging in P2P web search

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AU - Serdyukov, Pavel

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AU - Zimmer, C.

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AB - Intelligent Web search engines are extremely popular now. Currently, only the commercial centralized search engines like Google can process terabytes of Web data. Alternative search engines fulfilling collaborative Web search on a voluntary basis are usually based on a blooming Peer-to-Peer (P2P) technology. In this paper, we investigate the effectiveness of different database selection and result merging methods in the scope of P2P Web search engine Minerva. We adapt existing measures for database selection and results merging, all directly derived from popular document ranking measures, to address the specific issues of P2P Web search. We propose the general approach to both tasks based on the combination of pseudo-relevance feedback methods. From experiments with TREC Web data, we observe that the pseudo-relevance feedback information from the topically organized collections improves retrieval quality.

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Chernov S, Serdyukov P, Bender M, Michel S, Weikum G, Zimmer C. Database selection and result merging in P2P web search. In Proceedings of the 3rd International Workshop on Databases, Information Systems, and Peer-to-Peer Computing (DBISP2P 2005). Heidelberg, Germany: Springer. 2005. p. 26-37. 10.1007/978-3-540-71661-7_3. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-540-71661-7_3