Two Way Question Classification in Higher Education Domain
Автор: Vaishali Singh, Sanjay K. Dwivedi
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 9 vol.7, 2015 года.
Бесплатный доступ
Question classification plays vital role in Question Answering (QA) systems. The task of classifying a question to appropriate class is performed to predict the question type of the natural language question. In this paper, initially we have presented a brief overview of classification approaches adapted by different question answering systems so far and then propose a two-way question classification approach for higher education domain which not only identifies focus word and question class but also reduces answer search space within corpus comprise of question-answer pair, adding to the classification accuracy. For precise semantic interpretation of domain keywords, a domain specific dictionary is constructed which primarily have four domain word type. Classified features are built upon domain attributes in the form of constraints. The experiment proved the efficiency for restricted domain, even though we used quite simplistic approach.
Question answering system, question classification, question taxonomy, focus word, restricted domain, generic
Короткий адрес: https://sciup.org/15014796
IDR: 15014796
Список литературы Two Way Question Classification in Higher Education Domain
- Riloff E and Thelen M., A Rule-based Question Answering System for Reading Comprehension Tests. In ANLP /NAACL Workshop on Reading Comprehension Tests as Evaluation for Computer-Based Language Understanding Systems, Vol. 6, pp. 13-19, 2000.
- Singhal, A., Abney, S., Bacchiani, M., Collins, M., Hindle, D. & Pereira, F., In Proceedings of the 8th Text Retrieval Conference, NIST, 2000.
- Harabagiu, S. M., Moldovan, D. I., Pasca, M., Mihalcea, R., Surdeanu, M., Bunescu, R. C., Giriju, Rus, V. & Morarescu, P. FALCON: Boosting Knowledge for Answer Engines. In Proceedings of the 9th Text Retrieval Conference, NIST, Vol. 9, pp. 479-488, 2000.
- Li, X. & Roth, D., Learning question classifiers. In Proceedings of the 19th International Conference on Computational Linguistics (COLING 2002), pp.556-562, 2002.
- Katz, B., Lin, J. J., Loreto, D., Hildebrandt, W., Bilotti, M. W., Felshin, S., Fernandes, F., Marton, G., Mora, F., Integrating Web-based and Corpus-based Techniques for Question Answering. In TREC, pp. 426-435, 2003.
- Kaisser, M., and Becker, T., Question answering by searching large corpora with linguistic methods. In Proceedings of the 13th Text REtrieval Conference (TREC 2004), 2004.
- Xia, L., Teng, Z. & Ren, F., An Integrated Approach for Question classification in Chinese Cuisine Question Answering System, Second International Symposium on Universal Communication, 2008.
- Athenikos, S. J., Han, H., & Brooks, A. D., Semantic analysis and classification of medical questions for a logic-based medical question-answering system, In IEEE International Conference on Bioinformatics and Biomedicine Workshops, pp. 111-112, 2008.
- Han, L., Yu, Z. T., Qiu, Y. X., Meng, X. Y., Guo, J. Y., & Si, S. T. Research on passage retrieval using domain knowledge in Chinese question answering system. In IEEE International Conference on Machine Learning and Cybernetics, Vol. 5, pp. 2603-2606, 2008.
- Fu, J., Xu, J., & Jia, K., Domain ontology based automatic question answering. In IEEE International Conference on Computer Engineering and Technology, Vol. 2, pp. 346-349, 2009.
- Dang, N. T. & Tuyen D.T.T., Document Retrieval Based on Question Answering System. In IEEE Second International Conference Information and Computing Science, Vol. 1, pp. 183-186, 2009.
- Fakhr, M. S., & Abadeh, M. S., AISQA-An Artificial Immune Question Answering System. International Journal of Modern Education and Computer Science, Vol. 4(3), pp. 28-34, 2012.
- Arai, K., & Handayani, A. N., Question Answering for Collaborative Learning with Answer Quality Predictor. International Journal of Modern Education and Computer Science, 5(5), pp. 12-17, 2013.
- Mashat, A. F., Fouad, M. M., Philip, S. Y., & Gharib, T. F., Discovery of Association Rules from University Admission System Data. International Journal of Modern Education and Computer Science, 5(4), pp. 1-7, 2013.
- Dwivedi S.K. & Singh V., Integrated Question Classification based on Rules and Pattern Matching. In International Conference on Information and Communication Technology for Competative Strategies, 2014.
