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Fast and Effective Focused Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6203))

Abstract

Building an efficient and an effective search engine is a very challenging task. In this paper, we present the efficiency and effectiveness of our search engine at the INEX 2009 Efficiency and Ad Hoc Tracks. We have developed a simple and effective pruning method for fast query evaluation, and used a two-step process for Ad Hoc retrieval. The overall results from both tracks show that our search engine performs very competitively in terms of both efficiency and effectiveness.

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References

  1. Zobel, J., Moffat, A., Ramamohanarao, K.: Inverted files versus signature files for text indexing. ACM Trans. Database Syst. 23(4), 453–490 (1998)

    Article  Google Scholar 

  2. Zobel, J., Moffat, A.: Inverted files for text search engines. ACM Comput. Surv. 38(2), 6 (2006)

    Article  Google Scholar 

  3. Trotman, A.: Compressing inverted files. Inf. Retr. 6(1), 5–19 (2003)

    Article  Google Scholar 

  4. Anh, V.N., Moffat, A.: Inverted index compression using word-aligned binary codes. Inf. Retr. 8(1), 151–166 (2005)

    Article  Google Scholar 

  5. Anh, V.N., Moffat, A.: Improved word-aligned binary compression for text indexing. IEEE Transactions on Knowledge and Data Engineering 18(6), 857–861 (2006)

    Article  Google Scholar 

  6. Bovet, D.P., Cesati, M.: Understanding the linux kernel, 3rd edn. (November 2005)

    Google Scholar 

  7. Jia, X., Trotman, A., O’Keefe, R., Huang, Z.: Application-specific disk I/O optimisation for a search engine. In: PDCAT ’08: Proceedings of the 2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies, Washington, DC, USA, pp. 399–404. IEEE Computer Society, Los Alamitos (2008)

    Chapter  Google Scholar 

  8. Baeza-Yates, R., Gionis, A., Junqueira, F., Murdock, V., Plachouras, V., Silvestri, F.: The impact of caching on search engines. In: SIGIR ’07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 183–190. ACM, New York (2007)

    Chapter  Google Scholar 

  9. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval, pp. 513–523 (1988)

    Google Scholar 

  10. Lee, D.L., Chuang, H., Seamons, K.: Document ranking and the vector-space model. IEEE Softw. 14(2), 67–75 (1997)

    Article  Google Scholar 

  11. Harman, D., Candela, G.: Retrieving records from a gigabyte of text on a minicomputer using statistical ranking. Journal of the American Society for Information Science 41, 581–589 (1990)

    Article  Google Scholar 

  12. Buckley, C., Lewit, A.F.: Optimization of inverted vector searches, pp. 97–110 (1985)

    Google Scholar 

  13. Moffat, A., Zobel, J.: Self-indexing inverted files for fast text retrieval. ACM Trans. Inf. Syst. 14(4), 349–379 (1996)

    Article  Google Scholar 

  14. Persin, M.: Document filtering for fast ranking, pp. 339–348 (1994)

    Google Scholar 

  15. Persin, M., Zobel, J., Sacks-Davis, R.: Filtered document retrieval with frequency-sorted indexes. J. Am. Soc. Inf. Sci. 47(10), 749–764 (1996)

    Article  Google Scholar 

  16. Anh, V.N., de Kretser, O., Moffat, A.: Vector-space ranking with effective early termination, pp. 35–42 (2001)

    Google Scholar 

  17. Bentley, J.L., Mcilroy, M.D.: Engineering a sort function (1993)

    Google Scholar 

  18. Anh, V.N., Moffat, A.: Compressed inverted files with reduced decoding overheads, pp. 290–297 (1998)

    Google Scholar 

  19. Schenkel, R., Suchanek, F., Kasneci, G.: YAWN: A semantically annotated wikipedia xml corpus (March 2007)

    Google Scholar 

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Trotman, A., Jia, XF., Geva, S. (2010). Fast and Effective Focused Retrieval. In: Geva, S., Kamps, J., Trotman, A. (eds) Focused Retrieval and Evaluation. INEX 2009. Lecture Notes in Computer Science, vol 6203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14556-8_24

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  • DOI: https://doi.org/10.1007/978-3-642-14556-8_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14555-1

  • Online ISBN: 978-3-642-14556-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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