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ENSM-SE and UJM at INEX 2010: Scoring with Proximity and Tag Weights

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Comparative Evaluation of Focused Retrieval (INEX 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6932))

Abstract

This paper presents our participation in the Relevant in Context task (ad-hoc track) during the 2010 INEX competition, and a posterior analysis. Two models presented in previous editions of INEX by the authors were merged for our 2010 participation. The first one is based on the proximity of the query terms in the documents [1] and the second one is based on learnt tag weights [2]. The results demonstrate the improvement of focused information retrieval, thanks to the integration of the tag weights in the approach based on proximity.

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References

  1. Beigbeder, M.: Focused retrieval with proximity scoring. In: Proceedings of the 2010 ACM Symposium on Applied Computing, SAC 2010, pp. 1755–1759. ACM, New York (2010)

    Google Scholar 

  2. Géry, M., Largeron, C., Thollard, F.: Integrating structure in the probabilistic model for information retrieval. In: Web Intelligence, pp. 763–769 (2008)

    Google Scholar 

  3. Géry, M., Largeron, C., Thollard, F.: UJM at INEX 2008: Pre-impacting of tags weights. In: Geva, S., Kamps, J., Trotman, A. (eds.) INEX 2008. LNCS, vol. 5631, pp. 46–53. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  4. Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval, ch. 2. McGraw-Hill, New York (1983)

    MATH  Google Scholar 

  5. Hawking, D., Thistlewaite, P.: Proximity operators - so near and yet so far. In: [9]

    Google Scholar 

  6. Clarke, C.L.A., Cormack, G.V., Burkowski, F.J.: Shortest substring ranking (multitext experiments for TREC-4) In: [9]

    Google Scholar 

  7. Beigbeder, M., Mercier, A.: An information retrieval model using the fuzzy proximity degree of term occurences. In: Proceedings of the 2005 ACM Symposium on Applied Computing, SAC 2005, pp. 1018–1022. ACM, New York (2005)

    Google Scholar 

  8. Beigbeder, M., Imafouo, A., Mercier, A.: ENSM-SE at INEX 2009: Scoring with proximity and semantic tag information. In: Geva, S., Kamps, J., Trotman, A. (eds.) INEX 2009. LNCS, vol. 6203, pp. 49–58. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  9. Harman, D.K. (ed.): The Fourth Text REtrieval Conference (TREC-4), Department of Commerce, National Institute of Standards and Technology (1995)

    Google Scholar 

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Beigbeder, M., Géry, M., Largeron, C., Seck, H. (2011). ENSM-SE and UJM at INEX 2010: Scoring with Proximity and Tag Weights. In: Geva, S., Kamps, J., Schenkel, R., Trotman, A. (eds) Comparative Evaluation of Focused Retrieval. INEX 2010. Lecture Notes in Computer Science, vol 6932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23577-1_3

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  • DOI: https://doi.org/10.1007/978-3-642-23577-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23576-4

  • Online ISBN: 978-3-642-23577-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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