Can click patterns across user's query logs predict answers to definition questions?

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

Abstract

In this paper, we examined click patterns produced by users of Yahoo search engine when prompting definition questions. Regularities across these click patterns are then utilized for constructing a large and heterogeneous training corpus for answer ranking. In a nutshell, answers are extracted from clicked web-snippets originating from any class of web-site, including Knowledge Bases (KBs). On the other hand, nonanswers are acquired from redundant pieces of text across web-snippets. The effectiveness of this corpus was assessed via training two state-of-The-Art models, wherewith answers to unseen queries were distinguished. These testing queries were also submitted by search engine users, and their answer candidates were taken from their respective returned web-snippets. This corpus helped both techniques to finish with an accuracy higher than 70%, and to predict over 85% of the answers clicked by users. In particular, our results underline the importance of non-KB training data.

Original languageEnglish
Title of host publicationEACL 2012 - 13th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages99-108
Number of pages10
ISBN (Electronic)9781937284190
Publication statusPublished - 1 Jan 2012
Event13th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2012 - Avignon, France
Duration: 23 Apr 201227 Apr 2012

Publication series

NameEACL 2012 - 13th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings

Conference

Conference13th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2012
Country/TerritoryFrance
CityAvignon
Period23/04/1227/04/12

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

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