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AI Platform for Building University Research Knowledge Base

  • Jakub Koperwas
  • Łukasz Skonieczny
  • Marek Kozłowski
  • Piotr Andruszkiewicz
  • Henryk Rybiński
  • Wacław Struk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8502)

Abstract

This paper is devoted to the 3-years research performed at Warsaw University of Technology, aimed at building of an advanced software for university research knowledge base. As a result, a text mining platform has been built, enabling research in the areas of text mining and semantic information retrieval. In the paper some of the implemented methods are tested from the point of view of their applicability in a real life system.

Keywords

digital library artificial intelligence knowledge base scientific resources repository 

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References

  1. 1.
    Hazan, R., Andruszkiewicz, P.: Home Pages Identification and Information Extraction in Researcher Profiling. In: Bembenik, R., et al. (eds.) Intelligent Tools for Building a Scientific Information Platform: Advanced Architectures and Solutions, pp. 41–51 (2013)Google Scholar
  2. 2.
    Tang, J., Yao, L., Zhang, D., Zhang, J.: A combination approach to web user profiling. ACM Transactions on Knowledge Discovery from Data, TKDD 5(1), 2 (2010)Google Scholar
  3. 3.
    Bembenik, R., et al. (eds.): Intelligent Tools for Building a Scientific Information Platform. SCI, vol. 390. Springer, Heidelberg (2012)Google Scholar
  4. 4.
    Berman, F.: Got Data? A Guide to Data Preservation in the Information Age. CACM 51(12) (2008)Google Scholar
  5. 5.
    Gabrilowich, E., Markovitch, S.: Overcoming the brittleness bottleneck using Wikipedia: Enhancing text categorization with encyclopedic knowledge. AAAI (2006)Google Scholar
  6. 6.
    Gabrilowich, E., Markovitch, S.: Wikipedia-based semantic interpretation for natural language processing. Journal of Artificial Intelligence Research 34, 443–498 (2009)Google Scholar
  7. 7.
    Koperwas, J., Skonieczny, Ł., Rybiński, H., Struk, W.: Development of a University Knowledge Base. In: Bembenik, R., Skonieczny, Ł., Rybiński, H., Kryszkiewicz, M., Niezgódka, M. (eds.) Intell. Tools for Building a Scientific Information. SCI, vol. 467, pp. 97–110. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Koperwas, J., Skonieczny, Ł., Kozłowski, M., Rybiński, H., Struk, W.: University Knowledge Base – Two Years of Experience. In: Bembenik, R., Skonieczny, Ł., Rybin’ski, H., Kryszkiewicz, M., Niezgódka, M. (eds.) Intelligent Tools for Building a Scientific Information Platform - From Research to Implementation. SCI, vol. 541, pp. 257–274. Springer, Heidelberg (2014)Google Scholar
  9. 9.
    Kozłowski, M.: Word sense discovery using frequent termsets, PhD Thesis, Warsaw University of Technology (2014)Google Scholar
  10. 10.
    Di Marco, A., Navigli, R.: Clustering and Diversifying Web Search Results with Graph-Based Word Sense Induction, Computational Linguistics, vol. 39(3), pp. 709–754. MIT Press (2013)Google Scholar
  11. 11.
    Medelyan, O., Milne, D., Legg, C., Witten Ian, H.: Mining meaning from Wikipedia. Int’l. J. Hum.-Comput. Stud. 67(9), 716–754 (2009)CrossRefGoogle Scholar
  12. 12.
    Milne, D., Medelyan, O., Witten, I.H.: Mining domain-specific thesauri from Wikipedia: A case study. In: IEEE/WIC/ACM International Conference on Web Intelligence, Hong Kong, China, pp. 442–448 (2006)Google Scholar
  13. 13.
    Milne, D., Witten, I.H.: An effective, low-cost measure of semantic relatedness obtained from Wikipedia links. In: Wikipedia and Artificial Intelligence: An Evolving Synergy, Chicago, IL, pp. 25–30 (2008)Google Scholar
  14. 14.
    Navigli, R., Vannella, D.: SemEval-2013 Task 11: Word Sense Induction & Disambiguation within an End-User Applications. In: Proc. of 7th Int’l Workshop on Semantic Evaluation, 2nd Joint Conf. on Lexical and Computational Semantics, pp. 193–201 (2013)Google Scholar
  15. 15.
    Ontology of Scientific Journal, classification of scientific journals, http://www.science-metrix.com/eng/tools.htm
  16. 16.
    Omelczuk, A., Andruszkiewicz, P.: Agent-based Web Resource Retrieval System for Scientific Knowledge Base (2013)Google Scholar
  17. 17.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jakub Koperwas
    • 1
  • Łukasz Skonieczny
    • 1
  • Marek Kozłowski
    • 1
  • Piotr Andruszkiewicz
    • 1
  • Henryk Rybiński
    • 1
  • Wacław Struk
    • 1
  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarszawaPoland

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