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2017 | OriginalPaper | Buchkapitel

Gradually Improving the Computation of Semantic Textual Similarity in Portuguese

verfasst von : Hugo Gonçalo Oliveira, Ana Oliveira Alves, Ricardo Rodrigues

Erschienen in: Progress in Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

There is much research on Semantic Textual Similarity (STS) in English, specially since its inclusion in the SemEval evaluations. For other languages, it is not as common, mostly due to the unavailability of benchmarks. Recently, the ASSIN shared task targeted STS in Portuguese and released training and test collections. This paper describes an incremental approach to ASSIN, where the computed similarity is gradually improved by exploiting different features (e.g., token overlap, semantic relations, chunks, and negation) and approaches. The best reported results, obtained with a supervised approach, would get second place overall in ASSIN.

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Vorheriges Kapitel Unsupervised Approaches for Computing Word Similarity in Portuguese
Nächstes Kapitel Towards a Mention-Pair Model for Coreference Resolution in Portuguese
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Metadaten
Titel
Gradually Improving the Computation of Semantic Textual Similarity in Portuguese
verfasst von
Hugo Gonçalo Oliveira
Ana Oliveira Alves
Ricardo Rodrigues
Copyright-Jahr
2017
Buch
Progress in Artificial Intelligence

Print ISBN: 978-3-319-65339-6

Electronic ISBN: 978-3-319-65340-2

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-65340-2_68