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European Conference on Information Retrieval

ECIR 2005: Advances in Information Retrieval pp 540–542Cite as

Manipulating the Relevance Models of Existing Search Engines

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3408))

Abstract

Collaborative search refers to how the search behavior of communities of users can be used to influence the ranking of search results. In this poster we describe how this technique, as instantiated in the I-SPY meta-search engine can be used as a general mechanism for implementing a different relevance feedback strategy. We evaluate a relevance feedback strategy based on anchor-text and query similarity using the TREC2004 Terabyte track document collection.

This material is based on works supported by ScienceFoundation Ireland under Grant No. 03/IN.3/I361.

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References

  1. Freyne, J., Smyth, B., Coyle, M., Balfe, E., Briggs, P.: Further Experiments on Col- laborative Ranking in Community-Based Web Search. AI Review: An International Science and Engineering Journal 21(3-4), 229–252 (2004)

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  2. Balfe, E., Smyth, B.: Case Based Collaborative Web Search. In: Proceedings of the 7th European Conference on Cased Based Reasoning, pp. 489–503 (2004)

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  3. Blott, S., Boydell, O., Camous, F., Ferguson, P., Gaughan, G., Gurrin, C., Murphy, N., O’Connor, N., Smeaton, A.F., Smyth, B., Wilkins, P.: Experiments In Terabyte Searching, Genomic Retrieval And Novelty Detection For TREC-2004. In: Draft Proceedings of the Thirteenth Text REtrieval Conference (2004) (In Print)

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Author information

Authors and Affiliations

  1. Adaptive Information Cluster, Smart Media Institute, Department of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland

    Oisín Boydell & Barry Smyth

  2. Adaptive Information Cluster, Center for Digital Video Processing, Dublin City University, Glasnevin, Dublin 9, Ireland

    Cathal Gurrin & Alan F. Smeaton

Authors
  1. Oisín Boydell
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  2. Cathal Gurrin
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  3. Alan F. Smeaton
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  4. Barry Smyth
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Editor information

Editors and Affiliations

  1. Departamento de Electrónica y Computación, Universidad de Santiago de Compostela, Spain

    David E. Losada

  2. Departamento de Ciencias de la Computación e Inteligencia Artificial E.T.S.I. Informática y de Telecomunicación, Universidad de Granada, 18071, Granada, Spain

    Juan M. Fernández-Luna

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© 2005 Springer-Verlag Berlin Heidelberg

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Boydell, O., Gurrin, C., Smeaton, A.F., Smyth, B. (2005). Manipulating the Relevance Models of Existing Search Engines. In: Losada, D.E., Fernández-Luna, J.M. (eds) Advances in Information Retrieval. ECIR 2005. Lecture Notes in Computer Science, vol 3408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31865-1_44

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  • DOI: https://doi.org/10.1007/978-3-540-31865-1_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25295-5

  • Online ISBN: 978-3-540-31865-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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