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ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese

dc.contributor.authorAlves, Ana
dc.contributor.authorOliveira, Hugo Gonçalo
dc.contributor.authorRodrigues, Ricardo
dc.contributor.authorEncarnação, Rui
dc.date.accessioned2026-01-27T09:35:50Z
dc.date.available2026-01-27T09:35:50Z
dc.date.issued2018
dc.description.abstractSemantic Textual Similarity (STS) aims at computing the proximity of meaning transmitted by two sentences. In 2016, the ASSIN shared task targeted STS in Portuguese and released training and test collections. This paper describes the development of ASAPP, a system that participated in ASSIN, but has been improved since then, and now achieves the best results in this task. ASAPP learns a STS function from a broad range of lexical, syntactic, semantic and distributional features. This paper describes the features used in the current version of ASAPP, and how they are exploited in a regression algorithm to achieve the best published results for ASSIN to date, in both European and Brazilian Portuguese.eng
dc.identifier.doi10.4230/OASIcs.SLATE.2018.12
dc.identifier.urihttp://hdl.handle.net/10400.26/61204
dc.language.isoeng
dc.peerreviewedn/a
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectnatural language processing
dc.subjectsemantic textual similarity
dc.subjectsemantic relations
dc.subjectword embeddings
dc.subjectcharacter n-grams
dc.subjectsupervised machine learning
dc.titleASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portugueseeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage12:17
oaire.citation.startPage12:1
oaire.citation.title7th Symposium on Languages, Applications and Technologies (SLATE 2018)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRodrigues
person.givenNameRicardo
person.identifier.ciencia-idD31C-FB4A-FEAA
person.identifier.orcid0000-0002-6262-7920
relation.isAuthorOfPublicationc64ccf7c-eca2-43cf-a4a2-78e684499c00
relation.isAuthorOfPublication.latestForDiscoveryc64ccf7c-eca2-43cf-a4a2-78e684499c00

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