Detecting Paraphrases for Portuguese using Word and Sentence Embeddings

被引:3
|
作者
Souza, Marlo [1 ]
Sanches, Leandro M. P. [1 ]
机构
[1] Univ Fed Bahia, Salvador, BA, Brazil
来源
LINGUAMATICA | 2018年 / 10卷 / 02期
关键词
Paraphrase Identification; Semantic Textual Similarity; Sentence Embeddings;
D O I
10.21814/lm.10.2.286
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
Paraphrase detection/identification is the task of determining whether two or more sentences of arbitrary length possess the same meaning. Methods to solve this task have many potential applications in Natural Language Processing systems. This work investigates the combination of different methods of sentence representation in a vector space model of language and linear classifiers to the problem of paraphrase identification for the Portuguese language. The results obtained in this work are inferior to those obtained for the related task of recognizing textual entailment in the ASSIN evaluation for the Portuguese language, but we point out that in this work we investigate the application of sentence embeddings to the problem of paraphrase detection, as such other features usually explored in systems for this task may be trivially incorporated into our method to improve performance.
引用
收藏
页码:31 / 44
页数:14
相关论文
共 50 条
  • [31] Assessing Lexical-Semantic Regularities in Portuguese Word Embeddings
    Oliveira, Hugo Goncalo
    Sousa, Tiago
    Alves, Ana
    INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2021, 6 (05): : 34 - 46
  • [32] Semantic change and word embeddings: case studies on the diachrony of Portuguese
    Lage, Lucas Fonseca
    Teixeira Paradela Cunha, Evandro Landulfo
    REVISTA DE ESTUDOS DA LINGUAGEM, 2022, 30 (04)
  • [33] A Study on the Relevance of Generic Word Embeddings for Sentence Classification in Hepatic Surgery
    Oukelmoun, Achir
    Semmar, Nasredine
    de Chalendar, Gael
    Habran, Enguerrand
    Vibert, Eric
    Goblet, Emma
    Oukelmoun, Mariame
    Allard, Marc-Antoine
    2023 20TH ACS/IEEE INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, AICCSA, 2023,
  • [34] Performance Evaluation of Word and Sentence Embeddings for Finance Headlines Sentiment Analysis
    Mishev, Kostadin
    Gjorgjevikj, Ana
    Stojanov, Riste
    Mishkovski, Igor
    Vodenska, Irena
    Chitkushev, Ljubomir
    Trajanov, Dimitar
    ICT INNOVATIONS 2019: BIG DATA PROCESSING AND MINING, 2019, 1110 : 161 - 172
  • [35] Word Embeddings-based Sentence-Level Sentiment Analysis considering Word Importance
    Hayashi, Toshitaka
    Fujita, Hamido
    ACTA POLYTECHNICA HUNGARICA, 2019, 16 (07) : 7 - 24
  • [36] Extracting paraphrases of Japanese action word of sentence ending part from Web and mobile news articles
    Nakagawa, H
    Masuda, H
    INFORMATION RETRIEVAL TECHNOLOGY, 2005, 3411 : 94 - 105
  • [37] DefSent: Sentence Embeddings using Definition Sentences
    Tsukagoshi, Hayato
    Sasano, Ryohei
    Takeda, Koichi
    ACL-IJCNLP 2021: THE 59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 2, 2021, : 411 - 418
  • [38] Recognizing Textual Entailment and Paraphrases in Portuguese
    Rocha, Gil
    Cardoso, Henrique Lopes
    PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2017), 2017, 10423 : 868 - 879
  • [39] Portuguese Language Models and Word Embeddings: Evaluating on Semantic Similarity Tasks
    Rodrigues, Ruan Chaves
    Rodrigues, Jessica
    Quinta de Castro, Pedro Vitor
    Felipe da Silva, Nadia Felix
    Soares, Anderson
    COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE, PROPOR 2020, 2020, 12037 : 239 - 248
  • [40] Detecting Emerging Associations and Behaviors With Regional and Diachronic Word Embeddings
    Wolfe, Robert
    Caliskan, Aylin
    16TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2022), 2022, : 91 - 98