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Automatic Keyword Extraction Using Domain Knowledge

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Computational Linguistics and Intelligent Text Processing (CICLing 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2004))

Abstract

Documents can be assigned keywords by frequency analysis of the terms found in the document text, which arguably is the primary source of knowledge about the document itself. By including a hierarchi- cally organised domain specific thesaurus as a second knowledge source the quality of such keywords was improved considerably, as measured by match to previously manually assigned keywords. In the presented ex- periment, the combination of the evidence from frequency analysis and the hierarchically organised thesaurus was done using inductive logic programming.

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References

  1. Turney, P. D. (2000). Learning Algorithms for Keyphrase Extraction. Information Retrieval, 2(4):303–336. Kluwer Academic Publishers.

    Article  Google Scholar 

  2. Earl, L. L. (1970). Information Storage & Retrieval, volume 6, pp. 313–334. Pergamon Press.

    Article  Google Scholar 

  3. Luhn, H. P. (1957). A Statistical Approach to Mechanical Encoding and searching of Literary Information. IBM Journal of Research and Development, 1:309–317.

    Article  MathSciNet  Google Scholar 

  4. Luhn, H. P. (1959). Auto-Encoding of Documents for Information Retrieval Systems. In: Boaz. M. (ed.) Modern Trends in Documentation, pp. 45–58. Pergamon Press, London.

    Google Scholar 

  5. Mladenić, D. (1998). Turning Yahoo into an Automatic Web-Page Classifier. In: Prade, H. (ed.) 13th European Conference on Artificial Intelligence ECAI 98, pp. 473–474.

    Google Scholar 

  6. Boström, H. (2000). Manual for Virtual Predict 0.8, Virtual Genetics Inc.

    Google Scholar 

  7. Nienhuys-Cheng, S.-H., and de Wolf, R. (1997). Foundations of Inductive Logic Programming. LNAI 1228. Springer.

    Google Scholar 

  8. Freund Y., and Schapire R. E. (1996). Experiments with a new boosting algorithm. In: Machine Learning: Proceedings of the Thirteenth International Conference, pp. 148–156.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer and Systems Sciences, Stockholm University, Electrum 230, SE-164 40, Kista, Sweden

    Anette Hulth, Anna Jonsson, Henrik Boström & Lars Asker

  2. Swedish Institute of Computer Science, Box 1263, SE-164 29, Kista, Sweden

    Jussi Karlgren

  3. Virtual Genetics Laboratory, AB SE-171 77, Stockholm, Sweden

    Henrik Boström & Lars Asker

Authors
  1. Anette Hulth
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  2. Jussi Karlgren
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  3. Anna Jonsson
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  4. Henrik Boström
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  5. Lars Asker
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Editor information

Editors and Affiliations

  1. CIC (Centro de Investigación en Computatción IPN (Instituto Politécnico Nacional), Av. Juan Dios Bátiz s/n esq. M. Othon Mendizabal Col. Nuevo Vallejo, CP. 07738, México, Mexico

    Alexander Gelbukh (Unidad Profecional “Adolfo López Mateos”) (Unidad Profecional “Adolfo López Mateos”)

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© 2001 Springer-Verlag Berlin Heidelberg

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Hulth, A., Karlgren, J., Jonsson, A., Boström, H., Asker, L. (2001). Automatic Keyword Extraction Using Domain Knowledge. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2001. Lecture Notes in Computer Science, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44686-9_47

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  • DOI: https://doi.org/10.1007/3-540-44686-9_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41687-6

  • Online ISBN: 978-3-540-44686-6

  • eBook Packages: Springer Book Archive

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