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A random walk approach to selectional preferences based on preference ranking and propagation

  • Xi'an Jiaotong University

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

3 Scopus citations

Abstract

This paper presents an unsupervised random walk approach to alleviate data sparsity for selectional preferences. Based on the measure of preferences between predicates and arguments, the model aggregates all the transitions from a given predicate to its nearby predicates, and propagates their argument preferences as the given predicate's smoothed preferences. Experimental results show that this approach outperforms several state-of-the-art methods on the pseudo-disambiguation task, and it better correlates with human plausibility judgements.

Original languageEnglish
Title of host publicationLong Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages1169-1179
Number of pages11
ISBN (Print)9781937284503
StatePublished - 2013
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013

Publication series

NameACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Volume1

Conference

Conference51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
Country/TerritoryBulgaria
CitySofia
Period4/08/139/08/13

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