Using Clustering Approaches to Open-Domain Question Answering

  • Youzheng Wu
  • Hideki Kashioka
  • Jun Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4394)


This paper presents two novel clustering approaches and their application to open-domain question answering. The One-Sentence-Multi-Topic clustering approach is first presented, which clusters sentences to improve the language model for retrieving sentences. Second, regarding each cluster in the results for One-Sentence-Multi-Topic clustering as aligned sentences, we present a pattern-similarity-based clustering approach that automatically learns syntactic answer patterns to answer selection through vertical and horizontal clustering. Our experiments on Chinese question answering demonstrates that One-Sentence-Multi-Topic clustering is much better than K-Means and is comparable to PLSI when used in sentence clustering of question answering. Similarly, the pattern-similarity-based clustering also proved to be efficient in learning syntactic answer patterns, the absolute improvement in syntactic pattern-based answer extraction over retrieval-based answer extraction is about 9%.


Language Model Cluster Approach Pattern Cluster Question Type Question Answering 
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  1. 1.
    Moldovan, D., Harabagio, S., Girju, R., Morarescu, P., Lacatsu, F., Novischi, A.: LCC Tools for Question Answering. In: Proc. of TREC 2002 (2002)Google Scholar
  2. 2.
    Hovy, E.H., Hermjakob, U., Lin, C.Y.: The Use of External Knowledge of Factoid QA. In: Proc. of TREC 2001 (2001)Google Scholar
  3. 3.
    Ravichandran, D., Hovy, E.: Learning Surface Text Patterns for a Question Answering. In: Proc. of ACL Conference (2002)Google Scholar
  4. 4.
    Ittycheriah, A., Roukos, S.: IBM’s Statistical Question Answering System-TREC 11. In: Proc. of TREC, Gaithersburg, Maryland, November (2002)Google Scholar
  5. 5.
    Emmanuel, A.C., Croft, W.B., Murdock, V.: Answer Passage Retrieval for Question Answering. In: Proc. of SIGIR2004, pp. 516–517 (2004)Google Scholar
  6. 6.
    Murdock, V., Croft, W.B.: Simple Translation Models for Sentence Retrieval in Factoid Question Answering. In: Proc. of SIGIR2004 Workshop on IR4QA, pp. 31–35 (2004)Google Scholar
  7. 7.
    Nie, J.Y.: Integrating Term Relationships into Language Models for Information Retrieval. Report at ICT-CASGoogle Scholar
  8. 8.
    Voorhees, E.M.: Overview of the TREC 2004 Question Answering Track. In: Proc. of TREC 2004 (2004)Google Scholar
  9. 9.
    Soubbotin, M.M., Soubbotin, S.M.: Use of Patterns for Detection of Likely Answer Strings: A Systematic Approach. In: Proc. of TREC 2002, Maryland, November, (2002)Google Scholar
  10. 10.
    Dumais, S., Banko, M., Brill, E., Lin, J., Ng, A.: Web Question Answering: Is More Always Better? In: Proc. of SIGIR2002, Tampere, Finland, (2002)Google Scholar
  11. 11.
    Du, Y.P., Huang, X.J., Li, X., Wu, L.D., Novel, A.: Pattern Learning Method for Open Domain Question Answering. In: Proc. of IJCNLP2004, Sanya, China (2004)Google Scholar
  12. 12.
    Wu, Y.Z., Zhao, J., Duan, X.Y., Xu, B.: Building an Evaluation Platform for Chinese Question Answering Systems. In: Proc. of First NCIRCS2004, Shanghai (2004)Google Scholar
  13. 13.
    Wu, Y.Z., Zhao, J., Xu, B.: Chinese Named Entity Recognition Model Based on Multiple Features. In: Proc. of HLT/EMNLP 2005, Vancouver, Canada, pp. 427–434 (2005)Google Scholar
  14. 14.
    Duan, X.Y., Zhao, J., Xu, B.: Building Chinese Dependency Parser Using SVM. Term Report (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Youzheng Wu
    • 1
    • 2
  • Hideki Kashioka
    • 1
  • Jun Zhao
    • 2
  1. 1.NiCT-ATR 2-2-2 Hikaridai “Keihanna Science City” Kyoto 619-0288Japan
  2. 2.NLPR CASIA No.95 Zhongguancun East Road Beijing 100080China

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