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JRS’2012 Data Mining Competition: Topical Classification of Biomedical Research Papers

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Rough Sets and Current Trends in Computing (RSCTC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7413))

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Abstract

We summarize the JRS’2012 Data Mining Competition on “Topical Classification of Biomedical Research Papers”, held between January 2, 2012 and March 30, 2012 as an interactive on-line contest hosted on the TunedIT platform ( http://tunedit.org ). We present the scope and background of the challenge task, the evaluation procedure, the progress, and the results. We also present a scalable method for the contest data generation from biomedical research papers.

This work was partially supported by the grant N N516 077837 from the Ministry of Science and Higher Education of the Republic of Poland, the Polish National Science Centre grant 2011/01/B/ST6/03867 and by the Polish National Centre for Research and Development (NCBiR) under SYNAT – Grant No. SP/I/1/77065/10 in frame of the strategic scientific research and experimental development program: “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.

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References

  1. Roberts, R.J.: PubMed Central: The GenBank of the published literature. Proceedings of the National Academy of Sciences of the United States of America 98(2), 381–382 (2001)

    Article  Google Scholar 

  2. United States National Library of Medicine: Introduction to MeSH – 2011 (2011), http://www.nlm.nih.gov/mesh/introduction.html

  3. Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. In: Proceedings of the Twentieth International Joint Conference for Artificial Intelligence, Hyderabad, India, pp. 1606–1611 (2007)

    Google Scholar 

  4. Janusz, A., Świeboda, W., Krasuski, A., Nguyen, H.S.: Interactive Document Indexing Method Based on Explicit Semantic Analysis. In: Yao, J.T., et al. (eds.) RSCTC 2012. LNCS (LNAI), vol. 7413, pp. 156–165. Springer, Heidelberg (2012)

    Google Scholar 

  5. Ślęzak, D., Janusz, A., Świeboda, W., Nguyen, H.S., Bazan, J.G., Skowron, A.: Semantic Analytics of PubMed Content. In: Holzinger, A., Simonic, K.-M. (eds.) USAB 2011. LNCS, vol. 7058, pp. 63–74. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  6. Wojnarski, M., Stawicki, S., Wojnarowski, P.: TunedIT.org: System for Automated Evaluation of Algorithms in Repeatable Experiments. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS, vol. 6086, pp. 20–29. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. Wojnarski, M., Janusz, A., Nguyen, H.S., Bazan, J., Luo, C., Chen, Z., Hu, F., Wang, G., Guan, L., Luo, H., Gao, J., Shen, Y., Nikulin, V., Huang, T.-H., McLachlan, G.J., Bošnjak, M., Gamberger, D.: RSCTC’2010 Discovery Challenge: Mining DNA Microarray Data for Medical Diagnosis and Treatment. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS (LNAI), vol. 6086, pp. 4–19. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Janusz, A., Ślęzak, D., Nguyen, H.S.: Unsupervised similarity learning from textual data. Fundamenta Informaticae (2012)

    Google Scholar 

  9. Žbontar, J., Žitnik, M., Zidar, M., Majcen, G., Potočnik, M., Zupan, B.: Team ULjubljana’s Solution to the JRS 2012 Data Mining Competition. In: Yao, J.T., et al. (eds.) RSCTC 2012. LNCS (LNAI), vol. 7413, pp. 471–478. Springer, Heidelberg (2012)

    Google Scholar 

  10. Kowalski, M., Ślęzak, D., Stencel, K., Pardel, P., Grzegorowski, M., Kijowski, M.: RDBMS Model for Scientific Articles Analytics. In: Bembenik, R., Skonieczny, L., Rybiński, H., Niezgodka, M. (eds.) Intelligent Tools for Building a Scient. Info. Plat. SCI, vol. 390, pp. 49–60. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  11. Michel, S., Triantafillou, P., Weikum, G.: KLEE: a framework for distributed top-k query algorithms. In: Proceedings of the 31st International Conference on Very Large Data Bases, VLDB 2005, VLDB Endowment, pp. 637–648 (2005)

    Google Scholar 

  12. Krasuski, A., Szczuka, M.: Knowledge driven query sharding. In: 16th East-European Conference on Advances in Databases and Information Systems, Poznan, Poland, September 18-21 (2012) (submitted to conference)

    Google Scholar 

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Janusz, A., Nguyen, H.S., Ślęzak, D., Stawicki, S., Krasuski, A. (2012). JRS’2012 Data Mining Competition: Topical Classification of Biomedical Research Papers. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_50

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  • DOI: https://doi.org/10.1007/978-3-642-32115-3_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32114-6

  • Online ISBN: 978-3-642-32115-3

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