| Grant number: | 18/09465-0 |
| Support Opportunities: | Scholarships in Brazil - Master |
| Effective date (Start): | December 01, 2018 |
| Effective date (End): | January 31, 2020 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computer Systems |
| Acordo de Cooperação: | Coordination of Improvement of Higher Education Personnel (CAPES) |
| Principal Investigator: | Lilian Berton |
| Grantee: | Samuel Bruno da Silva Sousa |
| Host Institution: | Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil |
Abstract Word Sense Disambiguation (WSD) is an open problem of Natural Language Processing, which aims to identify the appropriate sense of a word in some context. Many approaches have been proposed to solve the problem, such as Knowledge-based, Supervised and Unsupervised Learning. Semi-Supervised Learning (SSL) has recently become an active research area that requires a small amount of labeled training data together with unlabeled data. In this project, we propose to employ graph-based SSL for WSD. The graph will be constructed given the senses of neighboring words. Then, a label propagation algorithm will be run on the graph-of-words to spread the sense from seed vertices to the unlabeled ones to attribute the most appropriate sense for each word. We will investigate different similarity measures for words/documents, propose new graph-of-words construction methods and analyze different label propagation algorithms. The proposed approaches will be evaluated in benchmark datasets, especially in all-words WSD task. | |
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