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A novel composite kernel for finding similar questions in CQA services

  • National University of Singapore
  • Beihang University

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

Abstract

Finding similar questions in Community Question Answering (CQA) services plays more and more important role in current web and IR applications. The task aims to retrieve historical questions that are similar or relevant to new questions posed by users. However, traditional "bag-of-words" based models would fail to measure the similarity between question sentences, as they usually ignore sequential and syntactic information. In this paper, we propose a novel composite kernel to improve the accuracy in question matching. Our study illustrate that the composite kernel can efficiently capture both lexical semantics and syntactic information in a question sentence by leveraging word sequence kernel, POS tag sequence kernel and syntactic tree kernel. Experimental results on real world datasets show that our proposed method significantly outperforms the state-of-the-art models.

Original languageEnglish
Title of host publicationWeb-Age Information Management - 11th International Conference, WAIM 2010, Proceedings
Pages608-619
Number of pages12
DOIs
StatePublished - 2010
Event11th International Conference on Web-Age Information Management, WAIM 2010 - Jiuzhaigou, China
Duration: 15 Jul 201017 Jul 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6184 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Web-Age Information Management, WAIM 2010
Country/TerritoryChina
CityJiuzhaigou
Period15/07/1017/07/10

Keywords

  • question answering
  • similarity measure
  • string kernel
  • tree kernel

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