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Quality of Semantic Compression in Classification

  • Conference paper
Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6421))

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Abstract

Article presents results of implementation of semantic compression for English. An idea of semantic compression is reintroduced with examples and steps taken to perform experiment are given. A task of re-engineering available structures in order to apply them to already existing project infrastructure for experiments is described. Experiment demonstrates validity of research along with real examples of semantically compressed documents.

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References

  1. Ceglarek, D., Haniewicz, K., Rutkowski, W.: Semantically Enchanced Intellectual Property Protection System - SEIPro2S. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS, vol. 5796, pp. 449–459. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  2. Ceglarek, D., Haniewicz, K., Rutkowski, W.: Semantic compression for specialised Information Retrieval systems. In: 2nd Asian Conference on Intelligent Information and Database Systems Studies in Computational Intelligence 283, Springer, Heidelberg (2010)

    Google Scholar 

  3. Baziz, M.: Towards a Semantic Representation of Documents by Ontology-Document Mapping (2004)

    Google Scholar 

  4. Baziz, M., Boughanen, M., Aussenac-Gilles, N.: Semantic Networks for a Conceptual Indexing of Documents. In: IR (2005)

    Google Scholar 

  5. Gonzalo, J., et al.: Indexing with WordNet Synsets can improve Text Retrieval (1998)

    Google Scholar 

  6. Hotho, A., Staab, S., Stumme, S.: Explaining Text Clustering Results using Semantic Structures. In: Lavrač, N., Gamberger, D., Todorovski, L., Blockeel, H. (eds.) PKDD 2003. LNCS (LNAI), vol. 2838, pp. 217–228. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  7. Hotho, A., Maedche, A., Staab, S.: Ontology-based Text Document Clustering. In: Proceedings of the Conference on Intelligent Information Systems. Springer, Zakopane (2003)

    Google Scholar 

  8. Khan, L., McLeod, D., Hovy, E.: Retrieval effectiveness of an ontology-based model for information selection (2004)

    Google Scholar 

  9. Krovetz, R., Croft, W.B.: Lexical Ambiguity and Information Retrieval (1992)

    Google Scholar 

  10. Frakes, W.B., Baeza-Yates, R.: Information Retrieval: Data Structures and Algorithms. Prentice-Hall, Englewood Cliffs (1992)

    Google Scholar 

  11. Fellbaum, C.: WordNet - An Electronic Lexical Database. The MIT Press, Cambridge (1998) ISBN:978-0-262-06197-1

    MATH  Google Scholar 

  12. Zellig, H.: Distributional Structure. Word 10(2/3), 146–162 (1954)

    Google Scholar 

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Ceglarek, D., Haniewicz, K., Rutkowski, W. (2010). Quality of Semantic Compression in Classification. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6421. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16693-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-16693-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16692-1

  • Online ISBN: 978-3-642-16693-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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