> Details

Alves, Ana [Author]; Gonçalo Oliveira, Hugo [Author]; Rodrigues, Ricardo [Author]; Encarnação, Rui [Author] ; Ana Alves and Hugo Gonçalo Oliveira and Ricardo Rodrigues and Rui Encarnação [Contributor]

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

Reference
management

Bookmarks

Remove from
bookmarks

Share this on Whatsapp

Close

Bookmarks



You can manage bookmarks using lists, please log in to your user account for this.
  • Media type: Text; E-Article; Electronic Conference Proceeding
  • Title: ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese
  • Contributor: Alves, Ana [Author]; Gonçalo Oliveira, Hugo [Author]; Rodrigues, Ricardo [Author]; Encarnação, Rui [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2018
  • Language: English
  • DOI: https://doi.org/10.4230/OASIcs.SLATE.2018.12
  • Keywords: character n-grams ; supervised machine learning ; word embeddings ; natural language processing ; semantic textual similarity ; semantic relations
  • Origination:
  • Footnote: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Description: 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.
  • Access State: Open Access