期刊
KNOWLEDGE-BASED SYSTEMS
卷 132, 期 -, 页码 47-61出版社
ELSEVIER
DOI: 10.1016/j.knosys.2017.06.013
关键词
Natural language processing; Graph-based; Knowledge-based; Word Sense Disambiguation; Pagerank
资金
- University of Alicante
- Generalitat Valenciana
- Spanish Government
- Ministerio de Educacion, Cultura y Deporte
- ASAP - Ayudas Fundacion BBVA a equipos de investigacion cientifica (FUNDACIONBBVA2-16PREMIO) [TIN2015-65100-R, TIN2015-65136-C2-2-R, PROMETEOII/2014/001, GRE16-01, PR16_SOC_0013]
This paper presents an unsupervised approach to solve semantic ambiguity based on the integration of the Personalized PageRank algorithm with word-sense frequency information. Natural Language tasks such as Machine Translation or Recommender Systems are likely to be enriched by our approach, which includes semantic information that obtains the appropriate word-sense via support from two sources: a multidimensional network that includes a set of different resources (i.e. WordNet, WordNet Domains, WordNet Affect, SUMO and Semantic Classes); and the information provided by word-sense frequencies and word-sense collocation from the SemCor Corpus. Our series of results were analyzed and compared against the results of several renowned studies using SensEval-2, SensEval-3 and SemEval-2013 datasets. After conducting several experiments, our procedure produced the best results in the unsupervised procedure category taking SensEval campaigns rankings as reference. (C) 2017 Elsevier B.V. All rights reserved.
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