Finding semantically similar questions based on their answers

ABSTRACT

A large number of question and answer pairs can be collected from question and answer boards and FAQ pages on the Web. This paper proposes an automatic method of finding the questions that have the same meaning. The method can detect semantically similar questions that have little word overlap because it calculates question-question similarities by using the corresponding answers as well as the questions. We develop two different similarity measures based on language modeling and compare them with the traditional similarity measures. Experimental results show that semantically similar questions pairs can be effectively found with the proposed similarity measures.

REFERENCES

• 1: Adam Berger , Rich Caruana , David Cohn , Dayne Freitag , Vibhu Mittal, Bridging the lexical chasm: statistical approaches to answer-finding, Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, p.192-199, July 24-28, 2000, Athens, Greece [doi>10.1145/345508.345576]
• 2: Jay M. Ponte , W. Bruce Croft, A language modeling approach to information retrieval, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, p.275-281, August 24-28, 1998, Melbourne, Australia [doi>10.1145/290941.291008]
• 3: K. Hammond , R. Burke , C. Martin , S. Lytinen, FAQ finder: a case-based approach to knowledge navigation, Proceedings of the 11th Conference on Artificial Intelligence for Applications, p.80, February 20-22, 1995

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.0 General

General Terms:
Algorithms, Experimentation, Measurement

Keywords:
FAQ retrieval, information retrieval, language models