Using Conceptual Graphs for Text Mining in Technical Support Services

  • Michael Bogatyrev
  • Alexey Kolosoff
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)

Abstract

Text mining problems of natural text classification and fact extraction are important in developing information systems for Technical Support Services. An approach which is based on joining acquisition of conceptual graphs and keywords search technique is presented to their solution. Conceptual graphs have been created from e-mail queries sent to Technical Support Service. Correct conceptual graphs acquired from e-mail texts represent facts and situations which become patterns to search in systems resources to resolve users problems. Experimental results of implementing proposed approach are presented.

Keywords

natural language texts classification conceptual graphs correctness of conceptual graphs technical support services 

References

  1. 1.
    Landauer, T., Foltz, P.W., Laham, D.: Introduction to Latent Semantic Analysis. Discourse Processes 25, 259–284 (1998)CrossRefGoogle Scholar
  2. 2.
    Ganter, B., Wille, R.: Formal Concept Analysis. Mathematical Foundations. Springer, Heidelberg (1999)CrossRefMATHGoogle Scholar
  3. 3.
    Sowa, J.F.: Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, London (1984)MATHGoogle Scholar
  4. 4.
    Salton, G., McGill, M.J.: Introduction to modern information retrieval. McGraw-Hill, New York (1983)MATHGoogle Scholar
  5. 5.
    Bogatyrev, M.Y., Mitrofanova, O.A., Tuhtin, V.V.: Building Conceptual Graphs for Articles Abstracts in Digital Libraries. In: Fourth Conceptual Structures Tool Interoperability Workshop (CS-TIW 2009) at 17th International Conference on Conceptual Structures (ICCS 2009), Moscow, pp. 50–57 (2009)Google Scholar
  6. 6.
    Gildea, D., Jurafsky, D.: Automatic labeling of semantic roles. Computational Linguistics 28, 245–288 (2002)CrossRefGoogle Scholar
  7. 7.
    Robertson, S., Walker, S., Jones, S., et al.: Okapi at TREC-3. In: Proceedings of the Third Text Retrieval Conference (TREC 1994), Gaithersburg, USA (1994)Google Scholar
  8. 8.
    Langit, L., Goff, K., Mauri, D., Malik, S.: Smart Business Intelligence Solutions with Microsoft SQL Server 2008. Microsoft Press (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Michael Bogatyrev
    • 1
  • Alexey Kolosoff
    • 1
  1. 1.Tula State UniversityTulaRussia

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