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Answering contextual questions based on ontologies and question templates

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Abstract

Contextual question answering (CQA), in which user information needs are satisfied through an interactive question answering (QA) dialog, has recently attracted more research attention. One challenge is to fuse contextual information into the understanding process of relevant questions. In this paper, a discourse structure is proposed to maintain semantic information, and approaches for recognition of relevancy type and fusion of contextual information according to relevancy type are proposed. The system is evaluated on real contextual QA data. The results show that better performance is achieved than a baseline system and almost the same performance as when these contextual phenomena are resolved manually. A detailed evaluation analysis is presented.

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References

  1. Tsuneaki K, Junichi F, Fumito M, Kando N. Handling information access dialogue through QA technologies — a novel challenge for open domain question answering. In: Proceedings of HLT-NAACL 2004 Workshop on Pragmatics in Question Answering. 2004, 70–77

  2. Chai J, Jin R. Discourse structure for context question answering. In: Proceedings of HLT-NAACL 2004 Workshop on Pragmatics of Question Answering. 2004, 23–30

  3. Carbonell J G. Discourse pragmatics and ellipsis resolution in taskoriented natural language interfaces. In: Proceedings of 21st Annual Meeting on Association for Computational Linguistics. 1983, 164–168

  4. Nils D, Jonsson A. Empirical studies of discourse representations for natural language interfaces. In: Proceedings of 4th Conference of the European Chapter of the ACL. 1989, 291–298

  5. Wang D S. A domain-specific question answering system based on ontology and question templates. In: Proceedings of 11th ACIS International Conference on Software Engineering. 2010, 151–156

  6. Fernlcndez R, Katagiri Y, Komatani K, Lemon O, Nakano M, eds. Proceedings of 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Stroudsburg: Association for Computational Linguistics, 2010

    Google Scholar 

  7. Chai J Y, Moore J D, Passonneau R J, Traum, D R, et al, eds. Proceedings of 12th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Stroudsburg: Association for Computational Linguistics, 2011

    Google Scholar 

  8. Mitkov R, Boguraev B K, Tait J I, Palmer M, eds. Journal of Natural Language Engineering, Special Issue on Interactive Question Answering, Cambridge: Cambridge University Press, 2009

    Google Scholar 

  9. Voorhees E M. Overview of the TREC 2001 question answering track. In: Proceedings of 10th Text Retrieval Conference. 2001, 42–51

  10. Mori T, Kawaguchi S, Ishioroshi M. Answering contextual questions based on the cohesion with knowledge. International Journal of Computer Processing Of Languages, 2007, 20(2/3): 115–135

    Google Scholar 

  11. Bernardi R, Kirschner M. From artificial questions to real user interaction logs: real challenges for interactive question answering systems. In: Proceedings of Workshop on Web Logs and Question Answering. 2010, 8–15

  12. Yang F, Feng J, DiFabbrizio G. A data driven approach to relevancy recognition for contextual question answering. In: Proceedings of HLT-NAACL 2006 Workshop on Interactive Question Answering. 2006, 33–40

  13. Kirschner M, Bernardi R, Baroni M, Dinh L T. Analyzing interactive QA dialogues using logistic regression models. In: Proceedings of XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence. 2009, 334–344

  14. Bernardi R, Kirschner M, Ratkovic Z. Context fusion: the role of discourse structure and centering theory. In: Proceedings of 19th International Conference on Language Resources and Evaluation. 2010, 2014–2021

  15. Kirschner M, Bernardi R. Towards an empirically motivated typology of follow-up questions: the role of dialogue context. In: Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue. 2010, 322–331

  16. Kato T, Fukumoto J, Masui F, Kando N. Are open-domain question answering technologies useful for information access dialogues? — an empirical study and a proposal of a novel challenge. ACM Transactions on Asian Language Information Processing, 2005, 4 (3): 243–262

    Article  Google Scholar 

  17. Van schooten B W, Op den akker R, Rosset S, Galibert O, Max A, Illouz G. Follow-up question handling in the IMIX and Ritel systems: A comparative study. Journal of Natural Language Engineering, 2009, 15(1):97–118

    Article  Google Scholar 

  18. Murata Y, Akiba T, Fujii A, Itou K. Question answering experiments at NTCIR-5: Acquisition of answer evaluation patterns and context processing using passage retrieval. In: Proceedings of the 5th NTCIR Workshop Meeting. 2005, 394–401

  19. Matsuda M, Fukumoto J. Answering questions of IAD task using reference resolution of follow-up questions. In: Proceedings of the 5th NTCIR Workshop Meeting. 2005, 414–421

  20. Hobbs J R. On the coherence and structure of discourse. Center for the Study of Language and Information from Leland Stanford Junior University. Report No. CSLI-85-37, 1985

  21. Mann WC, Thompson S A. Rhetorical structure theory: a theory of text organization. USC/ISI Technical Report ISI/RS-87-190, 1987

  22. Grosz B J, Sidner C. Attention, intention, and the structure of discourse. Computational Linguistics, 1986, 12(3): 175–204

    Google Scholar 

  23. Kamp H, Reyle U. From Discourse To Logic. Dordrecht: Kluwer Academic Publishers, 1993

    Book  Google Scholar 

  24. Lars A, Nils D, Jagonsson A. Discourse representation and discourse management for natural language interfaces. In: Proceedings of the 2nd Nordic Conference on Text Comprehension in Man and Machine. 1990, 1–14

  25. Quarteroni S, Manandhar S. Adaptivity in question answering with user modeling and a dialogue interface. In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics. 2006, 199–202

  26. Quarteroni S, Manandhar S. Designing an interactive open-domain question answering system. Journal of Natural Language Engineering, 2009, 15(1): 73–95

    Article  Google Scholar 

  27. Quarteroni S, Manandhar S. User modeling for personalized question answering. In: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence (AI*IA). 2007, 386–397

  28. Sun M, Chai J J. Towards intelligent QA interfaces: discourse processing for context questions. In: Proceedings of 11th International Conference on Intelligent User Interfaces. 2006, 163–170

  29. Noy N F, McGuinnes D L. Ontology development 101: a guide to creating your first ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report. 2001

  30. De Boni M, Manandhar S. Implementing clarification dialogues in open domain question answering. Journal of Natural Language Engineering, 2005, 11(4): 343–361

    Article  Google Scholar 

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Authors and Affiliations

  1. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China

    Dongsheng Wang

  2. Graduate University of the Chinese Academy of Sciences, Beijing, 100049, China

    Dongsheng Wang

  3. Department of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

    Dongsheng Wang

Authors
  1. Dongsheng Wang
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Correspondence to Dongsheng Wang.

Additional information

Dongsheng Wang received his bachelor and masters degree from Jiangsu University of Science and Technology in 2005 and 2007, respectively. Now he is a PhD candidate in Institute of Computing Technology, Chinese Academy of Science. His primary research interest is question answering and natural language understanding.

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Wang, D. Answering contextual questions based on ontologies and question templates. Front. Comput. Sci. China 5, 405–418 (2011). https://doi.org/10.1007/s11704-011-1031-9

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