Research output: Contribution to journal › Article › peer-review
The literature describes the Semantic Textual Similarity (STS) area as a fundamental part of many Natural Language Processing (NLP) tasks. The STS approaches are dependent on the availability of lexical-semantic resources. There are several efforts to improve the lexicalsemantics resources for the English language, and the state-of-art report a large amount of application for this language. Brazilian Portuguese linguistics resources, when compared with English ones, do not have the same availability regarding relation and contents, generation a loss of precision in STS tasks. Therefore, the current work presents an approach that combines Brazilian Portuguese and English lexical-semantics ontology resources to reach all potential of both language linguistic relations, to generate a language-mixture model to measure STS. We evaluated the proposed approach with a well-known and respected Brazilian Portuguese STS dataset, which brought to light some considerations about mixture models and their relations with ontology language semantics.
Translated title of the contribution | Семантическое сходство текстов на бразильском португальском языке: Подход, основанный на комбинировании нескольких языков |
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Original language | English |
Pages (from-to) | 235-244 |
Number of pages | 10 |
Journal | Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya |
Volume | 15 |
Issue number | 2 |
DOIs | |
State | Published - 1 Jan 2019 |
ID: 49087634