Enhancing Text Retrieval Semantically

  • Edgar B. Wendlandt
  • James R. Driscoll
Conference paper


Current information retrieval systems focus on the use of keywords to respond to user queries. We propose the additional use of surface level knowledge in order to improve the accuracy of information retrieval. Our approach is based on the database concept of semantic modeling (particularly entities and relationships among entities). We enhance the concept of query-document similarity by recognizing basic entity properties (attributes) which appear in text. We also enhance query-document similarity using the linguistic concept of thematic roles. Thematic roles allow us to recognize relationship properties which appear in text. We include several examples to illustrate our approach.


Inverse Document Frequency Thematic Role Document Vector Text Collection Entity Attribute 
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 Wien 1991

Authors and Affiliations

  • Edgar B. Wendlandt
    • 1
  • James R. Driscoll
    • 2
  1. 1.United States Coast GuardInformation Systems CenterAlexandriaUSA
  2. 2.Department of Computer ScienceUniversity of Central FloridaOrlandoUSA

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