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


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.


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


Supported by : 인하대학교


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