An Information Retrieval Approach Based on Discourse Type

  • D. Y. Wang
  • R. W. P. Luk
  • K. F. Wong
  • K. L. Kwok
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3999)


In ad hoc information retrieval (IR), some information need (e.g., find the advantages and disadvantages of smoking) requires the explicit identification of information related to the discourse type (e.g., advantages/ disadvantages) as well as to the topic (e.g., smoking). Such information need is not uncommon and may not be satisfied by using conventional retrieval methods. We extend existing retrieval models by adding a re-ranking strategy based on a novel graph-based retrieval model using document contexts that are called information units (IU). For evaluation, we focused on a discourse type that appeared in a subset of TREC topics where the retrieval effectiveness achieved by our conventional retrieval models for those topics was low. We showed that our approach is able to enhance the retrieval effectiveness for the selected TREC topics. This shows that our preliminary investigation is promising and deserves further investigation.


Information Retrieval Retrieval Model Query Term Retrieval Effectiveness Information Unit 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • D. Y. Wang
    • 1
  • R. W. P. Luk
    • 1
  • K. F. Wong
    • 2
  • K. L. Kwok
    • 3
  1. 1.Department of ComputingThe Hong Kong Polytechnic UniversityChina
  2. 2.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongChina
  3. 3.Information Retrieval Laboratory, Department of Computer Science, Queens CollegeCity University of New YorkUSA

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