Research output: Contribution to journal › Article › peer-review
Semantic Textual Similarity on Brazilian Portuguese : An approach based on language-mixture models. / Silva, A.; Lozkins, A.; Bertoldi, L.R.; Rigo, S.; Bure, V.M.
In: Vestnik Sankt-Peterburgskogo Universiteta, Prikladnaya Matematika, Informatika, Protsessy Upravleniya, Vol. 15, No. 2, 01.01.2019, p. 235-244.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Semantic Textual Similarity on Brazilian Portuguese
T2 - An approach based on language-mixture models
AU - Silva, A.
AU - Lozkins, A.
AU - Bertoldi, L.R.
AU - Rigo, S.
AU - Bure, V.M.
N1 - Silva A., Lozkins A., Bertoldi L. R., Rigo S., Bure V. M. Semantic Textual Similarity on Brazilian Portuguese: An approach based on language-mixture models. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2019, vol. 15, iss. 2, pp. 235–244. https://doi.org/10.21638/11702/spbu10.2019.207
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - computational linguistics
KW - natural language processing
KW - ontologies
KW - Semantic textual similarity
KW - компьютерная лингвистика
KW - обработка естественного языка
KW - онтологии
KW - семантическое сходство текстов
KW - computational linguistics
KW - natural language processing
KW - ontologies
KW - Semantic textual similarity
KW - компьютерная лингвистика
KW - обработка естественного языка
KW - онтологии
KW - семантическое сходство текстов
UR - http://www.scopus.com/inward/record.url?scp=85074893286&partnerID=8YFLogxK
U2 - 10.21638/11702/spbu10.2019.207
DO - 10.21638/11702/spbu10.2019.207
M3 - Article
AN - SCOPUS:85074893286
VL - 15
SP - 235
EP - 244
JO - ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ
JF - ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ
SN - 1811-9905
IS - 2
ER -
ID: 49087634