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DOI: 10.4230/OASIcs.SLATE.2018.12
ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese

Authors: Ana Alves, Hugo Gonçalo Oliveira, Ricardo Rodrigues, and Rui Encarnação

Published in: OASIcs, Volume 62, 7th Symposium on Languages, Applications and Technologies (SLATE 2018)

Abstract
Semantic 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.
Cite as

Ana Alves, Hugo Gonçalo Oliveira, Ricardo Rodrigues, and Rui Encarnação. ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese. In 7th Symposium on Languages, Applications and Technologies (SLATE 2018). Open Access Series in Informatics (OASIcs), Volume 62, pp. 12:1-12:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{alves_et_al:OASIcs.SLATE.2018.12,
  author =	{Alves, Ana and Gon\c{c}alo Oliveira, Hugo and Rodrigues, Ricardo and Encarna\c{c}\~{a}o, Rui},
  title =	{{ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese}},
  booktitle =	{7th Symposium on Languages, Applications and Technologies (SLATE 2018)},
  pages =	{12:1--12:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-072-9},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{62},
  editor =	{Henriques, Pedro Rangel and Leal, Jos\'{e} Paulo and Leit\~{a}o, Ant\'{o}nio Menezes and Guinovart, Xavier G\'{o}mez},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2018.12},
  URN =		{urn:nbn:de:0030-drops-92709},
  doi =		{10.4230/OASIcs.SLATE.2018.12},
  annote =	{Keywords: natural language processing, semantic textual similarity, semantic relations, word embeddings, character n-grams, supervised machine learning}
}
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