A combination of rule and supervised learning approach to recognize paraphrases

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 par...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 1; pp. 110 - 115
Main Authors Bing-Quan Liu, Shuai Xu, Bao-Xun Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Application software
Audio systems
Computer science
Cybernetics
Information retrieval
Machine learning
Natural languages
Paraphrase
Psychology
Question answering
Semantic similarity
Supervised learning
Syntactic structure
Wounds
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Summary: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.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212543