Semantically Enhanced Intellectual Property Protection System - SEIPro2S

  • Dariusz Ceglarek
  • Konstanty Haniewicz
  • Wojciech Rutkowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5796)


The aim of this work is to present some of the capabilities of a Semantically Intellectual Enhanced Property Protection System. The system has reached a prototype phase where experiments are possible. It uses an extensive semantic net algorithms for Polish language that enable it to detect similarities in two compared documents on a level far beyond simple text matching. SEIPro2S benefits both from using a local document repository and from Web based resources. Main focus of this work is to give a reader overview of architecture and some actual results.


intellectual property semantic net thought matching natural language processing 


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  1. 1.
    Ah-Hwae, T., Fon-Lin, L.: Text Categorization, Supervised Learning, and Domain Knowledge Integration (2004)Google Scholar
  2. 2.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, Addison-Wesley Longman Publishing Co, New York (1999)Google Scholar
  3. 3.
    Ballinger, K.: .NET Web Services, Architecture and Implementation. Pearson Education, London (2003)Google Scholar
  4. 4.
    Baziz, M.: Towards a Semantic Representation of Documents by Ontology-Document Mapping (2004)Google Scholar
  5. 5.
    Baziz, M., Boughanen, M., Aussenac-Gilles, N.: Semantic Networks for a Conceptual Indexing of Documents in IR (2005)Google Scholar
  6. 6.
    Ben-Ari, M.: Principles of Concurrent and Distributed Programming, 2nd edn. Pearson Education (2005)Google Scholar
  7. 7.
    Ceglarek, D.: Zastosowanie sieci semantycznej do disambiguacji pojec w jezyku naturalnym, red. In: Porebska-Miac T., Sroka H. (eds.). w: Systemy wspomagania organizacji SWO 2006 - Katowice: Wydawnictwo Akademii Ekonomicznej (AE) w Katowicach (2006)Google Scholar
  8. 8.
    Frakes, W.B., Baeza-Yates, R.: Information Retrieval - Data Structures and Algorithms. Prentice Hall, Englewood Cliffs (1992)Google Scholar
  9. 9.
    Gonzalo, J., et al.: Indexing with WordNet Synsets can improve Text Retrieval (1998)Google Scholar
  10. 10.
    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)CrossRefGoogle Scholar
  11. 11.
    Labuzek, M.: Wykorzystanie metamodelowania do specyfikacji ontologii znaczenia opisow rzeczywistosci, projekt badawczy KBN (2004)Google Scholar
  12. 12.
    Khan, L., McLeod, D., Hovy, E.: Retrieval effectiveness of an ontology-based model for information selection (2004)Google Scholar
  13. 13.
    Krafzig, D., Banke, K., Slama, D.: Enterprise SOA. Prentice Hall, Englewood Cliffs (2005)Google Scholar
  14. 14.
    Krovetz, R., Croft, W.B.: Lexical Ambiguity and Information Retrieval (1992)Google Scholar
  15. 15.
    Sanderson, M.: Word Sense Disambiguation and Information Retrieval (1997)Google Scholar
  16. 16.
    Sanderson, M.: Retrieving with Good Sense (2000)Google Scholar
  17. 17.
    Stokoe, C., Oakes, M.P., Tait, J.: Word Sense Disambiguation in Information Retrieval Revisited. In: SIGIR 2003 (2003)Google Scholar
  18. 18.
    Van Bakel, B.: Modern Classical Document Indexing. A linguistic contribution to knowledge-based IR (1999)Google Scholar
  19. 19.
    Gale, W., Church, K., Yarowsky, D.: A Method for Disambiguating Word Senses in a Large Corpus. Computers and the Humanities 26, 415–439 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Dariusz Ceglarek
    • 1
  • Konstanty Haniewicz
    • 2
  • Wojciech Rutkowski
    • 3
  1. 1.Wyzsza Szkola Bankowa w PoznaniuPoland
  2. 2.Uniwersytet Ekonomiczny w PoznaniuPoland
  3. 3.Business Consulting CenterPoland

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