Evaluating Smoothing Algorithms against Plausibility Judgements

Maria Lapata, Frank Keller, Scott McDonald

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Previous research has shown that the plausibility of an adjective-noun combination is correlated with its corpus co-occurrence frequency. In this paper, we estimate the co-occurrence frequencies of adjective-noun pairs that fail to occur in a 100 million word corpus using smoothing techniques and compare them to human plausibility ratings. Both class-based smoothing and distance-weighted averaging yield frequency estimates that are significant predictors of rated plausibility, which provides independent evidence for the
validity of these smoothing techniques.
Original languageEnglish
Title of host publicationProceedings of the 39th Annual Meeting of the Association for Computational Linguistics
PublisherAssociation for Computational Linguistics
Pages346-353
Number of pages8
Publication statusPublished - 2001
Event39th Annual Meeting of the Association for Computational Linguistics - Toulouse, France
Duration: 6 Jul 201111 Jul 2011

Conference

Conference39th Annual Meeting of the Association for Computational Linguistics
Country/TerritoryFrance
Period6/07/1111/07/11

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