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Semantic Fuzzy Implication Operator for Semantic Implication Relationship of Knowledge Descriptions in Question Answering System

질의 응답 시스템에서 지식 설명의 의미적 포함 관계를 고려한 의미적 퍼지 함의 연산자

  • 안찬민 (인하대학교 IT공과대학 컴퓨터정보공학부) ;
  • 이주홍 (인하대학교 IT공과대학 컴퓨터정보공학부) ;
  • 최범기 (인하대학교 IT공과대학 컴퓨터정보공학부) ;
  • 박선 (목포대학교 MTRC 센터 정보산업연구소)
  • Received : 2011.01.21
  • Accepted : 2011.03.16
  • Published : 2011.03.28

Abstract

The question answering system shows the answers that are input by other users for user's question. In spite of many researches to try to enhance the satisfaction level of answers for user question, there is a essential limitation. So, the question answering system provides users with the method of recommendation of another questions that can satisfy user's intention with high probability as an auxiliary function. The method using the fuzzy relational product operator was proposed for recommending the questions that can includes largely the contents of the user's question. The fuzzy relational product operator is composed of the Kleene-Dienes operator to measure the implication degree by contents between two questions. However, Kleene-Dienes operator is not fit to be the right operator for finding a question answers pair that semantically includes a user question, because it was not designed for the purpose of finding the degree of semantic inclusion between two documents. We present a novel fuzzy implication operator that is designed for the purpose of finding question answer pairs by considering implication relation. The new operator calculates a degree that the question semantically implies the other question. We show the experimental results that the probability that users are satisfied with the searched results is increased when the proposed operator is used for recommending of question answering system.

Keywords

Question Answering System;Fuzzy Relational Product Operator;Semantic Fuzzy Implication Operator;Question Recommendation

Acknowledgement

Supported by : 인하대학교

References

  1. C. M. Ahn, J. H. Lee, B. G. Choi, and S. Park, "Question Answering System with Recommendation using Fuzzy Relational Product Operator," Proc. of Information Integration and Web-based Applications & Services, pp.853-856, 2010. https://doi.org/10.1145/1967486.1967633
  2. J. Bian, Y. Liu, E. Agichtein, and H. Zha, "Finding the right facts in the crowd: factoid question answering over social media," Proc. of the 17th international conference on World Wide Web, 2008. https://doi.org/10.1145/1367497.1367561
  3. Z. Gyongyi, G. Koutrika, J. Pedersen, and H. Garcia-Molina, "Questioning Yahoo! Answers," First Workshop on Question Answering on the Web at the 17th International World Wide Web Conference, 2008
  4. D. Hu, S. Wang, L. Wenyin, and E. Chen, "Question recommendation for user-interactive question answering systems," Proc. of the 2nd int. conf. on Ubiquitous information management and communication, pp.39-44, 2008. https://doi.org/10.1145/1352793.1352803
  5. M. Liu, Y. Liu, and Q. Yang, "Searching semantically similar questions from a large community based question archive," International Conference on Natural Language Processing and Knowledge Engineering, pp.1-8, 2009. https://doi.org/10.1109/NLPKE.2009.5313808
  6. K. K. Nam, M. S. Ackerman, and L. A. Adamic, "Questions in, Knowledge iN? A Study of Naver's Question Answering Community," Proc. of the 27th international conference on Human factors in computing systems, 2009.
  7. K. W. Oh and W. Bandler, "Properties of fuzzy implication operators," International Journal of Approximate Reasoning, Vol.1, No3, pp.273-285, 1987. https://doi.org/10.1016/S0888-613X(87)80002-6
  8. S. E. Robertson, S. Walker, Jones S., M. M. Hancock-Beaulieu, and M. Gatford, "Okapi at TREC-3," Proc. of the 3rd Text Retrieval Conference, 1995.
  9. E. M. Voorhees, "Overview of the TREC 2002 Question Answering Track," Proc. of the 11th Text Retrieval Conference, 2002.
  10. C. Shah and J. Pomerantz, "Evaluating and predicting answer quality in community QA," Proc. of the 33rd international ACM SIGIR conference on Research and development in information retrieval, pp.411-418, 2010.
  11. J. W. Jeon, W. B. Croft, J. H. Lee, and S. Park, "A Framework to Predict the Quality of Answers with Non-Textual Features," Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, pp.228-235, 2006.
  12. P. Jurczyk and E. Agichtein, "Discovering authorities in question answer communities by using link analysis," Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, 2007.
  13. Hang Cui, Mi. Y. Kan, and T. S. Chua, "Soft Pattern Matching Models for Definitional Question Answering," ACM Transactions on Information Systems (TOIS), Vol.25, No.2, 2007(4). https://doi.org/10.1145/1229179.1229182
  14. K. W. Kor and T. S. Chua, "Interesting Nuggets and Their Impact on Definitional Question Answering," Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, pp.335-342, 2007. https://doi.org/10.1145/1277741.1277800
  15. M. Harper, D. Raban, S. Rafaeli, and J. A. Konstan, "Predictors of answer quality in online Q&A sites," Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, pp.865-874, 2008.
  16. 안찬민, 최범기, 전석주, 이주홍, 이정식, “지식 검색 시스템에 적용 가능한 추천 질의 시스템", 한국정보교육학회논문지, 제14권, 제3호, pp.405-416, 2010.