Deep analysis of word sense disambiguation via semi-supervised learning and neural word representations

Author:

Duarte José Marcio,Sousa Samuel,Milios Evangelos,Berton Lilian

Funder

Natural Sciences and Engineering Research Council of Canada

State of Sao Paulo Research Foundation

Dalhousie University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference48 articles.

1. E. Agirre, P. Edmonds, Word Sense Disambiguation: Algorithms and Applications, Springer Publishing Company, Incorporated, 1st edn., ISBN 1402068700, 2007.

2. A. Alexandrescu, K. Kirchhoff, Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP, in: NAACL-HLT, ACL, 204–211, 2007.

3. O. Baskaya, D. Jurgens, Semi-supervised Learning with Induced Word Senses for State of the Art Word Sense Disambiguation, J. Artif. Int. Res. 55 (1) (2016) 1025–1058, ISSN 1076–9757.

4. L. Berton, A. de Andrade Lopes, D.A. Vega-Oliveros, A Comparison of Graph Construction Methods for Semi-Supervised Learning, in: 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, ISSN 2161–4407, 1–8, 2018.

5. From word to sense embeddings: a survey on vector representations of meaning;Camacho-Collados;J. Artif. Intell. Res.,2018

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