title: Semantic Textual Similarity on Brazilian Portuguese: An approach based on language-mixture models
metadata.name: dc.contributor.author
metadata.value: Silva, Allan
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Lozkins, Aleksejs
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Bertoldi, Luiz Ricardo
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Rigo, Sandro
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Bure, Vladimir M.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2019-07-17T12:16:13Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2019-07-17T12:16:13Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2019-06
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: 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.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2019.207
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/15957
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: 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.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 15; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: Semantic Textual Similarity
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: natural language processing
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: computational linguistics
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: ontologies
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Semantic Textual Similarity on Brazilian Portuguese: An approach based on language-mixture models
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 235-244.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/15957/1/235-244.pdf
resources.format: Adobe PDF
resources.size: 322,33 kB