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Explorando métodos non-supervisados para calcular a similitude semántica textual
Author(s) -
Pablo Gamallo,
Martín Pereira-Fariña
Publication year - 2019
Publication title -
linguamática
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.121
H-Index - 7
ISSN - 1647-0818
DOI - 10.21814/lm.10.2.275
Subject(s) - humanities , philosophy , similitude , computer science , artificial intelligence
galegoNeste traballo presentanse varios metodos non-supervisados para a deteccion da similitude semantica textual, os cales estan baseados en modelos distribucionais e no parseado de dependencias. Os sistemas son avaliados mediante datasets empregados na ASSIN Shared Task, celebrada conxuntamente co PROPOR 2016. Os metodos mais basicos ofrecen un mellor comportamento que aqueles, mais complexos, que incluen informacion sintactico-semantica na analise das oracions. Por ultimo, o uso de modelos distribucionais construidos automaticamente a partir de corpus ofrece resultados comparabeis as estratexias que utilizan recursos lexicos externos construidos manualmente. EnglishThis paper presents some unsupervised methods for detecting semantic textual similarity, which are based on distributional models and dependency parsing. The systems are evaluated using the dataset realased by the ASSIN Shared Task co-located with PROPOR 2016. The more basic methods offer better behavior than the more complex ones, which include syntactic-semantic information in sentence analysis. Finally, the use of distributional models built automatically from corpora provides results comparable to strategies that use external lexical resources built manually.

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