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2014 | 2 | 27--34
Tytuł artykułu

Adaptive Learning for Improving Semantic Tagging of Scientific Articles

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper we consider a problem of automatic labeling of textual data with concepts explicitly defined in an external knowledge base. We describe our tagging system and we also present a framework for adaptive learning of associations between terms or phrases from the texts and the concepts. Those associations are then utilized by our semantic interpreter, which is based on the Explicit Semantic Analysis (ESA) method, in order to label scientific articles indexed by our SONCA platform. Apart from the description of the learning algorithm, we show a few practical application examples of our system, in which it was used for tagging scientific articles with headings from the MeSH ontology, categories from ACM Computing Classification System and from OECD Fields of Science and Technology Classification.(original abstract)
Rocznik
Tom
2
Strony
27--34
Opis fizyczny
Twórcy
  • University of Warsaw, Poland
  • University of Warsaw, Poland
  • University of Warsaw, Poland
Bibliografia
  • "Revised Field of Science and Technology (FoS) Classification in the Frascati Manual," Committee for Scientific and Technological Policy, Directorate for Science, Technology and Industry, OECD, Feb. 2007.
  • Association for Computing Machinery, "The 2012 acm computing classification system," Online: http://www.acm.org/about/class/2012, 2012. [Online]. Available: http://www.acm.org/about/class/2012
  • Bembenik R., Skonieczny L., Rybinski H., Kryszkiewicz M., Niezgodka M., Eds., Intelligent Tools for Building a Scientific Information Platform - Advanced Architectures and Solutions, ser. Studies in Computational Intelligence. Springer, 2013, vol. 467.
  • Egozi O., Markovitch S., Gabrilovich E., "Concept-based information retrieval using explicit semantic analysis," ACM Trans. Inf. Syst., vol. 29, no. 2, pp. 8:1-8:34, Apr. 2011. [Online]. Available: http://doi.acm.org/10.1145/1961209.1961211
  • Fazzinga B., Gianforme G., Gottlob G., Lukasiewicz T., "Semantic web search based on ontological conjunctive queries," Web Semantics: Science, Services and Agents on the World Wide Web, 2011.
  • Gabrilovich E., Markovitch S., "Computing semantic relatedness using wikipedia-based explicit semantic analysis," in Proc. of The 20th Int. Joint Conf. on Artificial Intelligence, Hyderabad, India, 2007, pp. 1606-1611. [Online]. Available: http://www.cs.technion.ac.il/~shaulm/papers/pdf/Gabrilovich-Markovitch-ijcai2007.pdf
  • Hastie T., Tibshirani R., Friedman J., The Elements of Statistical Learning, ser. Springer Series in Statistics. New York, NY, USA: Springer New York Inc., 2001.
  • Hliaoutakis A., Varelas G., Voutsakis E., Petrakis E. G.M., Milios E., "Information retrieval by semantic similarity," Int. Journal on Semantic Web and Information Systems (IJSWIS). Special Issue of Multimedia Semantics, vol. 3, no. 3, pp. 55-73, 2006.
  • Janusz A., Nguyen H.S., Ślęzak D., Stawicki S., Krasuski A., "JRS'2012 Data Mining Competition: Topical Classification of Biomedical Research Papers," in Proceedings of the 8th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2012), Chengdu, China, August 17-20, 2012, ser. LNAI, J.T. Yao et al., Ed., vol. 7413. Springer, Heidelberg, 2012, pp. 417-426.
  • Janusz A., Świeboda W., Krasuski A., Nguyen H.S., "Interactive document indexing method based on Explicit Semantic Analysis," in Proceedings of the 8th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2012), Chengdu, China, August 17-20, 2012, ser. LNAI, J.T. Yao et al., Ed., vol. 7413. Springer, Heidelberg, 2012, pp. 156-165.
  • Manning C.D., Raghavan P., Schütze H., Introduction to Information Retrieval. New York, NY, USA: Cambridge University Press, 2008.
  • Mitchell T.M., Machine Learning, ser. McGraw Hill series in computer science. McGraw-Hill, 1997.
  • Nguyen L.A., Nguyen H.S., "On designing the sonca system," in Intelligent Tools for Building a Scientific Information Platform, R. Bembenik, L. Skonieczny, H. Rybíński, and M. Niezgódka, Eds. Springer-Verlag New York, 2012, pp. 9-36.
  • Rinaldi A.M., "An ontology-driven approach for semantic information retrieval on the web," ACM Trans. Internet Technol., vol. 9, pp. 1-24, 2009. [Online]. Available: http://doi.acm.org/10.1145/1552291.1552293
  • Roberts R.J., "PubMed Central: The GenBank of the published literature," Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 2, pp. 381-382, 2001. [Online]. Available: http://www.pnas.org/content/98/2/381.abstract
  • Ślęzak D., Janusz A., Świeboda W., Nguyen H.S., Bazan J.G., Skowron A., "Semantic analytics of PubMed content," in Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Graz, Austria, November 25-26, 2011. Proceedings, ser. LNCS, A. Holzinger and K.-M. Simonic, Eds., vol. 7058. Springer, 2011, pp. 63-74.
  • United States National Library of Medicine, "Introduction to MeSH - 2011," Online: http://www.nlm.nih.gov/mesh/introduction.html, 2011. [Online]. Available: http://www.nlm.nih.gov/mesh/introduction.html
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171299831

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