By Florentina T. Hristea
ISBN-10: 3642336922
ISBN-13: 9783642336928
This e-book offers contemporary advances (from 2008 to 2012) touching on use of the Naïve Bayes version in unsupervised observe feel disambiguation (WSD).
While WSD, normally, has a couple of very important purposes in a variety of fields of synthetic intelligence (information retrieval, textual content processing, computer translation, message knowing, man-machine conversation etc.), unsupervised WSD is taken into account very important since it is language-independent and doesn't require formerly annotated corpora. The Naïve Bayes version has been commonplace in supervised WSD, yet its use in unsupervised WSD has ended in extra modest disambiguation effects and has been much less widespread. it appears the opportunity of this statistical version with admire to unsupervised WSD maintains to stay insufficiently explored.
The current publication contends that the Naïve Bayes version should be fed wisdom which will practice good as a clustering process for unsupervised WSD and examines 3 totally varied assets of such wisdom for function choice: WordNet, dependency family members and internet N-grams. WSD with an underlying Naïve Bayes version is eventually located at the border among unsupervised and knowledge-based strategies. some great benefits of feeding wisdom (of numerous natures) to a knowledge-lean set of rules for unsupervised WSD that makes use of the Naïve Bayes version as clustering procedure are basically highlighted. The dialogue exhibits that the Naïve Bayes version nonetheless holds promise for the open challenge of unsupervised WSD.
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The Naïve Bayes Model for Unsupervised Word Sense Disambiguation: Aspects Concerning Feature Selection (SpringerBriefs in Statistics) by Florentina T. Hristea
by Daniel
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