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Hits 1 – 2 of 2
1
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features ...
Billami, Mokhtar
. - : arXiv, 2017
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Approches d'analyse distributionnelle pour améliorer la désambiguïsation sémantique ...
Billami, Mokhtar
;
Gala, Núria
. - : arXiv, 2017
Abstract:
Word sense disambiguation (WSD) improves many Natural Language Processing (NLP) applications such as Information Retrieval, Machine Translation or Lexical Simplification. WSD is the ability of determining a word sense among different ones within a polysemic lexical unit taking into account the context. The most straightforward approach uses a semantic proximity measure between the word sense candidates of the target word and those of its context. Such a method very easily entails a combinatorial explosion. In this paper, we propose two methods based on distributional analysis which enable to reduce the exponential complexity without losing the coherence. We present a comparison between the selection of distributional neighbors and the linearly nearest neighbors. The figures obtained show that selecting distributional neighbors leads to better results. ... : in French, Journ'ees internationales d'Analyse statistique des Donn'ees Textuelles (JADT), Jun 2016, Nice, France ...
Keyword:
Computation and Language cs.CL
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FOS Computer and information sciences
URL:
https://dx.doi.org/10.48550/arxiv.1702.08451
https://arxiv.org/abs/1702.08451
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