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An Answer Validation Concept Based Approach for Question Answering in Biomedical Domain

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Modern Advances in Applied Intelligence (IEA/AIE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8481))

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Abstract

With the continuously growing literatures in the biomedical domain, it is not feasible for researchers to manually go through all information for answering questions. The task of making knowledge contained in texts in forms that machines can use for automated processing is more and more important. This paper describes a system to answer multiple-choice questions for the biomedical domain while reading a given document. In this study, we use the data from the pilot task “machine reading of biomedical texts about Alzheimer’s disease” which is a task of the Question Answering for Machine Reading Evaluation (QA4MRE) Lab at CLEF 2012. We adapt the concept of answer validation that assumes the over-generation hypotheses will be checked in the validation step. In the following, the query expansion technique “global analysis” is applied. The best result is 0.51 c@1 score which is clearly above the baseline at CLEF 2012 and shows an exhilarating performance.

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References

  1. Voorhees, E.M., Tice, D.M.: The TREC-8 Question Answering Track Evaluation. In: Proceedings of Text Retrieval Conference TREC-8, pp. 83–105 (1999)

    Google Scholar 

  2. IBM Watson: IBM (2011), http://www-03.ibm.com/innovation/us/watson/

  3. Xu, B., Lin, H., Liu, B.: Study on Question Answering System for Biomedical Domain. In: Proceedings of IEEE 2009 International Conference on Granular Computing (GrC 2009), pp. 626–629 (2009)

    Google Scholar 

  4. Hirschman, L., Gaizauskas, R.: Natural Language Question Answering: the View from Here. Nat. Lang. Eng. 7, 275–300 (2001)

    Article  Google Scholar 

  5. Cao, Y., Liu, F., Simpson, P., Antieau, L., Bennett, A., Cimino, J.J., Ely, J., Yu, H.: AskHERMES: an Online Question Answering System for Complex Clinical Questions. J. Biomed. Inform. 44(2), 277–288 (2011)

    Article  Google Scholar 

  6. Gobeill, J., Patsche, E., Theodoro, D., Veuthey, A.-L., Lovis, C., Ruch, P.: Question Answering for Biology and Medicine. In: Proceedings of the 9th International Conference on Information Technology and Applications in Biomedicine (ITAB 2009), pp. 1–5 (2009)

    Google Scholar 

  7. Yu, H., Lee, M., Kaufman, D., Ely, J., Osheroff, J.A., Hripcsak, G., Cimino, J.: Development, Implementation, and a Cognitive Evaluation of a Definition Question Answering System for Physicians. J. Biomed. Inform. 40(3), 236–251 (2007)

    Article  Google Scholar 

  8. Demner-Fushman, D., Lin, J.: Answering Clinical Questions with Knowledge-based and Statistical Techniques. Comput. Linguist. 33(1), 63–103 (2007)

    Article  Google Scholar 

  9. Delbecque, T., Jacquemart, P., Zweigenbaum, P.: Indexing UMLS Semantic Types for Medical Question-Answering. Stud. Health Technol. Inform. 116, 805–810 (2005)

    Google Scholar 

  10. Weiming, W., Hu, D., Feng, M., Wenyin, M.: Automatic Clinical Question Answering Based on UMLS Relations. In: Proceedings of the Third International Conference on Semantics, Knowledge and Grid (SKG 2007), pp. 495–498 (2007)

    Google Scholar 

  11. Slaughter, L.A., Soergel, D., Rindflesch, T.C.: Semantic Representation of Consumer Questions and Physician Answers. Int. J. Med. Inform. 75, 513–529 (2006)

    Article  Google Scholar 

  12. Terol, R.M., Martinez-Barco, P., Palomar, M.: A Knowledge Based Method for the Medical Question Answering Problem. Comput. Biol. Med. 27, 1511–1521 (2007)

    Article  Google Scholar 

  13. Yu, H., Lee, M.: Accessing Bioscience Images from Abstract Sentences. Bioinformatics 22(14), e547–e565 (2006)

    Article  Google Scholar 

  14. Demner-Fushman, D., Few, B., Hauser, S.E., Thoma, G.: Automatically Identifying Health Outcome Information in MEDLINE Records. J. Am. Med. Inform. Assoc. 13(1), 52–60 (2006)

    Article  Google Scholar 

  15. Shi, Z., Melli, G., Wang, Y., Liu, Y., Gu, B., Kashani, M.M., Sarkar, A., Popowich, F.: Question Answering Summarization of Multiple Biomedical Documents. In: Proceedings of the 20th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (CAI 2007), pp. 284–295 (2007)

    Google Scholar 

  16. Rinaldi, F., Dowdall, J., Schneider, G., Persidis, A.: Answering Questions in the Genomics Domain. In: Proceedings of the ACL-2004 Workshop Question Answering in Restricted Domains, pp. 46–53 (2004)

    Google Scholar 

  17. Kontos, J., Lekakis, J., Malagardi, I., Peros, J.: Grammars for Question Answering Systems Based on Intelligent Text Mining in Biomedicine. In: Proceedings of the 7th Hellenic European Conf. Computer Mathematics and Its Applications (HERCMA (2005), http://www.aueb.gr/pympe/hercma/proceedings2005/H05-FULL-PAPERS-1/KONTOS-LEKAKIS-MALAGARDI-PEROS-1.pdf

  18. Morante, R., Krallinger, M., Valencia, A., Daelemans, W.: Machine Reading of Biomedical Texts about Alzheimer’s Disease. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  19. Attardi, G., Atzori, L., Simi, M.L.: Index Expansion for Machine Reading and Question Answering. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  20. Bhattacharya, S., Toldo, L.: Question Answering for Alzheimer Disease Using Information Retrieval. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  21. Grau, B., Pho, V.M., Ligozat, A.L., Abacha, A.B., Zweigenbaum, P., Chowdhury, F.: Adaptation of LIMSI’s QALC for QA4MRE. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  22. Vishnyakova, D., Gobeill, J., Ruch, P.: Using a Question-Answering in Machine Reading Task of Biomedical Texts About the Alzheimer Disease. In: CLEF 2013 Evaluation Labs and Workshop - Working Notes Papers (2013)

    Google Scholar 

  23. Martinez, D., MacKinlay, A., Molla-Aliod, D., Cavedon, L., Verspoor, K.: Simple Similarity-based Question Answering Strategies for Biomedical Text. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  24. Tsai, B.H., Hou, W.J.: Biomedical Text Mining about Alzheimer’s Diseases for Machine Reading Evaluation. In: CLEF 2012 Evaluation Labs and Workshop - Working Notes Papers (2012)

    Google Scholar 

  25. Patel, A., Yang, Z., Nyberg, E., Mitamura, T.: Building an Optimal Question Answering System Automatically Using Configuration Space Exploration (CSE) for QA4MRE 2013 Tasks. In: CLEF 2013 Evaluation Labs and Workshop - Working Notes Papers (2013)

    Google Scholar 

  26. Qiu, Y., Frei, H.P.: Concept Based Query Expansion. In: Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 160–169 (1993)

    Google Scholar 

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Hou, WJ., Tsai, BH. (2014). An Answer Validation Concept Based Approach for Question Answering in Biomedical Domain. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8481. Springer, Cham. https://doi.org/10.1007/978-3-319-07455-9_16

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  • DOI: https://doi.org/10.1007/978-3-319-07455-9_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07454-2

  • Online ISBN: 978-3-319-07455-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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