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Diversifying Information Needs in Results of Question Retrieval

  • Harbin Institute of Technology Shenzhen

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

Abstract

Information need is an important factor in question retrieval. This paper proposes a method to diversify the results of question retrieval in term of types of information needs. CogQTaxo, a question hierarchy is leveraged to represent users' information needs cognitively from three linguistic levels. Based on a prediction model of question types, three factors, i.e., scores of IR model, question type similarity and question type novelty are linearly combined to re-rank the retrieved questions. Preliminary experimental results show that the proposed method enhances the question retrieval performance in information coverage and diversity.

Original languageEnglish
Title of host publicationIJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing
EditorsHaifeng Wang, David Yarowsky
PublisherAssociation for Computational Linguistics (ACL)
Pages1432-1436
Number of pages5
ISBN (Electronic)9789744665645
StatePublished - 2011
Externally publishedYes
Event5th International Joint Conference on Natural Language Processing, IJCNLP 2011 - Chiang Mai, Thailand
Duration: 8 Nov 201113 Nov 2011

Publication series

NameIJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing

Conference

Conference5th International Joint Conference on Natural Language Processing, IJCNLP 2011
Country/TerritoryThailand
CityChiang Mai
Period8/11/1113/11/11

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