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Improvements to Suffix Tree Clustering

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Advances in Information Retrieval (ECIR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8416))

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Abstract

We investigate document clustering through adaptation of Zamir and Etzioni’s method for Suffix Tree Clustering. We modified it with substantial improvements in effectiveness and efficiency compared to the original algorithm.

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References

  1. Chim, H., Deng, X.: A New Suffix Tree Similarity Measure for Document Clustering. In: Proceedings of the 16th international conference on World Wide Web, pp. 121–130. ACM, New York (2007)

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  2. Zu Eissen, S.M., Stein, B., Potthast, M.: The Suffix Tree Document Model Revisited. In: Tochtermann, M. (ed.) Proceedings of the I-KNOW 2005, Graz 5th International Conference on Knowledge Management Journal of Universal Computer Science, pp. 596–603 (2005)

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  3. Gulla, Borch, Ingvaldsen: Contextualized Clustering in Exploratory Web Search. In: do Prado, H.A., Ferneda, E. (eds.) Emerging Technologies of Text Mining: Techniques and Applications, pp. 184–207. IGI Global (2007)

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  4. Moe, R., Elgesem, D.: Compact trie clustering for overlap detection in news. In: Proceedings of NIK 2013 (2013)

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  5. Smyth, B.: Computing Patterns in Strings. Addison Wesley (2003)

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  6. Zamir, O., Etzioni, O.: Web Document Clustering: A Feasibility Demonstration. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 46–54. ACM, New York (1998)

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Author information

Authors and Affiliations

  1. Department of Information Science and Media Studies, University of Bergen, Norway

    Richard Elling Moe

Authors
  1. Richard Elling Moe
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Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Maarten de Rijke  & Tom Kenter  & 

  2. Centrum Wiskunde en Informatica, Amsterdam, The Netherlands and Delft University of Technology, Delft, The Netherlands

    Arjen P. de Vries

  3. University of Illinois at Urbana-Champaign, Urbana, IL, USA

    ChengXiang Zhai

  4. University of Twente, Twente, The Netheralnds and Erasmus University Rotterdam, Rotterdam, The Netherlands

    Franciska de Jong

  5. SalesPredict, Haifa, Israel

    Kira Radinsky

  6. Microsoft Research, Cambridge, UK

    Katja Hofmann

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© 2014 Springer International Publishing Switzerland

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Moe, R.E. (2014). Improvements to Suffix Tree Clustering. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_73

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  • DOI: https://doi.org/10.1007/978-3-319-06028-6_73

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06027-9

  • Online ISBN: 978-3-319-06028-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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