Gradually Improving the Computation of Semantic Textual Similarity in Portuguese

被引:2
作者
Oliveira, Hugo Goncalo [1 ]
Alves, Ana Oliveira [1 ,2 ]
Rodrigues, Ricardo [1 ,3 ]
机构
[1] Univ Coimbra, DEI, CISUC, Coimbra, Portugal
[2] Polytech Inst Coimbra, ISEC, Coimbra, Portugal
[3] Polytech Inst Coimbra, ESEC, Coimbra, Portugal
来源
PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2017) | 2017年 / 10423卷
关键词
Natural language processing; Semantic Textual Similarity; Semantic relations; Supervised machine learning;
D O I
10.1007/978-3-319-65340-2_68
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:841 / 854
页数:14
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