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A combination of rule and supervised learning approach to recognize paraphrases

  • Bing Quan Liu*
  • , Shuai Xu
  • , Bao Xun Wang
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Paraphrase recognition is the basic of paraphrase researches. However, most of the existing researches mainly focus on the acquirement of paraphrases from a certain text corpus, or their methods are restricted to certain conditions. There is not a method that can decide whether two sentences are paraphrases generally. This paper presents a combination of rule and supervised learning method to recognize paraphrases. In this method, we make use of the classification of paraphrases and adopt different approaches to recognize paraphrases according to the types they belong to. And the key point is how to use a variety of strategies to get the semantic similarity of two sentences. As the system is mainly for Question Answering (QA), evaluations are conducted on a corpus of sentence pairs mainly collected from a QA system, Baidu zhidao. Results show that the precision exceeds 75% on the simple sentences whose syntax analyses are correct, which is significantly higher than most of the existing methods.

Original languageEnglish
Title of host publicationProceedings of the 2009 International Conference on Machine Learning and Cybernetics
PublisherIEEE Computer Society
Pages110-115
Number of pages6
ISBN (Print)9781424437030
DOIs
StatePublished - 2009
Externally publishedYes
Event8th International Conference on Machine Learning and Cybernetics, ICMLC 2009 - Baoding, China
Duration: 12 Jul 200915 Jul 2009

Publication series

NameProceedings of the 2009 International Conference on Machine Learning and Cybernetics
Volume1

Conference

Conference8th International Conference on Machine Learning and Cybernetics, ICMLC 2009
Country/TerritoryChina
CityBaoding
Period12/07/0915/07/09

Keywords

  • Paraphrase
  • Question answering
  • Semantic similarity
  • Syntactic structure

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