Applying RST Relations to Semantic Search

  • Nguyen Thanh Tri
  • Akira Shimazu
  • Le Cuong Anh
  • Nguyen Minh Le
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4188)


This paper proposes a new way of extracting answers to some kinds of queries based on Rhetorical Structure Theory (RST). For each type of question, we assign one or more rhetorical relations that help extract the corresponding answers. We use ternary expressions which are successfully applied in the well-known question answering system START to represent text segments, index documents and queries. The cosine measure is used in the matching process. The experiment with RST Discourse Treebank shows that the results of ternary-expression-based indexing are better than those of keyword-based indexing.


Question Type Text Segment Factual Question Cosine Measure Index Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Katz, B.: Using English for Indexing and Retrieving. In: Proceedings of the 1st RIAO Conference on User-Oriented Content-Based Text and Image Handling (1988)Google Scholar
  2. 2.
    Clark, C., et al.: Question Answering by Passage Selection. In: The 9th Text REtrieval Conference (TREC 2000), pp. 229–235 (2000)Google Scholar
  3. 3.
    Mann, W., Thompson, S.: Rhetorical Structure Theory: A theory of text organization. In: Polanyi, L. (ed.) Discourse structure, pp. 85–96. Ablex, Norwood (1987)Google Scholar
  4. 4.
    Marcu, D.: The Rhetorical Parsing of Unrestricted Texts: A Surface-Based Approach. Computational Linguistics 26(3), 395–448 (2000)CrossRefGoogle Scholar
  5. 5.
    Bonino, D., et al.: DOSE: a Distributed Open Semantic Elaboration Platform. In: The 15th IEEE International Conference on Tools with Artificial Intelligence, Sacramento, California (2003)Google Scholar
  6. 6.
    Voorhees, E.: Overview of TREC 2003. In: The Twelfth Text Retrieval Conference (TREC 2003), pp. 1–13 (2003)Google Scholar
  7. 7.
    Heflin, J., Hendler, J.: Searching the Web with SHOE. In: Artificial Intelligence for Web Search. Papers from the AAAI Workshop, WS-00-01, pp. 35–40. AAAI Press, Menlo Park (2000)Google Scholar
  8. 8.
    Le Thanh, H.: Investigation into an approach to automatic text summarization. Doctoral dissertation, Middlesex University (2004)Google Scholar
  9. 9.
    Carlson, L., et al.: Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory. In: van Kuppevelt, J., Smith, R. (eds.) Current Directions in Discourse and Dialogue, pp. 85–112. Kluwer Academic Publishers, Dordrecht (2003)Google Scholar
  10. 10.
    Colhen, S., et al.: XSearch: A semantic search engine for XML. In: The 29th International Conference on Very Large Databases (VLDB) (2003)Google Scholar
  11. 11.
    Nomoto, T.: Machine Learning Approaches to Rhetorical Parsing and Open-Domain Text Summarization. Doctoral Dissertation, Nara Institute of Science and Technology (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nguyen Thanh Tri
    • 1
  • Akira Shimazu
    • 1
  • Le Cuong Anh
    • 1
  • Nguyen Minh Le
    • 1
  1. 1.School of Information ScienceJapan Advanced Institute of Science and TechnologyNomi, IshikawaJapan

Personalised recommendations