Traditional resources help interpret texts

ABSTRACT

Simple word matching between the user query and document is common, as are mis-matches of meaning that occur as a consequence, and errors in recall. These defects in the "bag of words" model are well known, and raising the semantic level of representation will improve retrieval. This can be done by expanding words and user queries using traditional reference sources such as gazetteers and synonym lists or ontologies.

REFERENCES

• 1: H. Schütze, Dimensions of meaning, Proceedings of the 1992 ACM/IEEE conference on Supercomputing, p.787-796, November 16-20, 1992, Minneapolis, Minnesota, United States
• 2: Michael Lesk, Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone, Proceedings of the 5th annual international conference on Systems documentation, p.24-26, June 1986, Toronto, Ontario, Canada [doi>10.1145/318723.318728]
• 3: T. K. Landauer , K. M. Galotti , S. Hartwell, Natural command names and initial learning: a study of text-editing terms, Communications of the ACM, v.26 n.7, p.495-503, July 1983 [doi>10.1145/358150.358157]
• 4: Carr, N. 2008. Is Google making us stupid? Atlantic, July-August. Retrieved August 5 from http://www.theatlantic.com/doc/200807/google
• 5: Will Hill , Larry Stead , Mark Rosenstein , George Furnas, Recommending and evaluating choices in a virtual community of use, Proceedings of the SIGCHI conference on Human factors in computing systems, p.194-201, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223929]
• 6: Berners-Lee, T., J. Hendler, and O. Lassila. 2001. The Semantic Web. Scientific American, 16 pp. Retrieved August 6 from http://wwwpersonal.si.umich.edu/~rfrost/courses/SI110/readings/In_Out_and_Beyond/Semantic_Web.pdf.
• 7: Winchester, S. 1998. The Professor and the Madman. HarperCollins.
• 8: Murray, E. 2001. Caught in the Web of Words. Yale University Press.
• 9: McArthur, T. 1986. Worlds of Reference. Cambridge University Press.
• 10: Fellbaum, C. 1998. Wordnet: An Electronic Lexical Database. MIT Press.
• 11: Gelernter, J. 2008. MapSearch: a protocol and prototype application to find maps. PhD thesis, Rutgers University.
• 12: Richard W. Hamming, Numerical Methods for Scientists and Engineers, McGraw-Hill, Inc., New York, NY, 1973
• 13: Leidner, J. Topnym Resolution in Text. Edinburgh PhD thesis, 2007.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Thesauruses

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

General Terms:
Human Factors, Performance

Keywords:
information retrieval, knowledge representation, ontologies