A question answer system using mails posted to a mailing list

ABSTRACT

The most serious difficulty in developing a QA system is knowledge. In this paper we first discuss three problems of developing a knowledge base by which a QA system answers how type questions. Then we propose a method of developing a knowledge base by using mails posted to a mailing list. Next we describe a QA system which can answer how type questions based on the knowledge base. Our system finds question mails which are similar to user's question and shows the answers to the user. The similarity between user's question and a question mail is calculated by matching of user's question and a significant sentence in the question mail. Finally we show that mails posted to a mailing list can be used as a knowledge base by which a QA system answers how type questions.

REFERENCES

• 1: TREC (Text REtrieval Conference): http://trec.nist.gov/
• 2: NTCIR (NII-NACSIS Test Collection for IR Systems) project: http://research.nii.ac.jp/ntcir/index-en.html
• 3: Sadao Kurohashi , Wataru Higasa, Dialogue helpsystem based on flexible matching of user query with natural language knowledge base, Proceedings of the 1st SIGdial workshop on Discourse and dialogue, p.141-149, October 07-08, 2000, Hong Kong [doi>10.3115/1117736.1117752]
• 4: Yoji Kiyota , Sadao Kurohashi , Fuyuko Kido, "Dialog Navigator": a question answering system based on large text knowledge base, Proceedings of the 19th international conference on Computational linguistics, p.1-7, August 24-September 01, 2002, Taipei, Taiwan [doi>10.3115/1072228.1072312]
• 5: Sadao Kurohashi , Makoto Nagao, A syntactic analysis method of long Japanese sentences based on the detection of conjunctive structures, Computational Linguistics, v.20 n.4, p.507-534, December 1994
• 6: Kurohashi and Nagao: JUMAN Manual version 3.6 (in Japanese) Nagao Lab. Kyoto University (1998).

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing

General Terms:
Languages

Keywords:
mailing list, question answer system, sentence extraction