Human-inspired semantic similarity between sentences

被引:1
|
作者
Ignacio Serrano, J. [1 ]
Dolores del Castillo, M. [1 ]
Oliva, Jesus [2 ]
Raya, Rafael [1 ]
机构
[1] CSIC, Grp Neural & Cognit Engn gNeC, Ctr Automat & Robot, Barcelona, Spain
[2] BBVA Data & Analyt, Barcelona, Spain
关键词
Cognitive linguistics; Computational linguistics; Semantic similarity;
D O I
10.1016/j.bica.2015.04.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Following the Principle of Compositionality, the meaning of a complex expression is influenced, to some extent, not only by the meanings of its individual words, but also the structural way the words are assembled. Compositionality has been a central research issue for linguists and psycholinguists. However, it remains unclear how does syntax influence the meaning of a sentence. In this paper, we propose an interdisciplinary approach to better understand that relation. We present an empirical study that seeks for the different weights given by humans to different syntactic roles when computing semantic similarity. In order to test the validity of the hypotheses derived from the psychological study, we use a computational paradigm. We incorporate the results of that study to a psychologically plausible computational measure of semantic similarity. The results shown by this measure in terms of correlation with human judgments on a paraphrase recognition task confirm the different importance that humans give to different syntactic roles in the computation of semantic similarity. This results contrast with generative grammar theories but support neurolinguistic evidence. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:121 / 133
页数:13
相关论文
共 50 条
  • [1] SEMANTIC SIMILARITY BETWEEN SENTENCES
    HONECK, RP
    JOURNAL OF PSYCHOLINGUISTIC RESEARCH, 1973, 2 (02) : 137 - 151
  • [2] A Human-Inspired Model to Represent Uncertain Knowledge in the Semantic Web
    Pileggi, Salvatore Flavio
    COMPUTATIONAL SCIENCE - ICCS 2018, PT III, 2018, 10862 : 254 - 268
  • [3] Human-inspired robots
    Coradeschi, Silvia
    Ishiguro, Hiroshi
    Asada, Minoru
    Shapiro, Stuart C.
    Thielscher, Michael
    Breazeal, Cynthia
    Mataric, Maja J.
    Ishida, Hiroshi
    IEEE INTELLIGENT SYSTEMS, 2006, 21 (04) : 74 - 85
  • [4] Supervised Learning to Measure the Semantic Similarity Between Arabic Sentences
    Wali, Wafa
    Gargouri, Bilel
    Ben Hamadou, Abdelmajid
    COMPUTATIONAL COLLECTIVE INTELLIGENCE (ICCCI 2015), PT I, 2015, 9329 : 158 - 167
  • [5] Semantic similarity between sentences through approximate tree matching
    Ribadas, FJ
    Vilares, M
    Vilares, J
    PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS, 2005, 3523 : 638 - 646
  • [6] Human-inspired computational fairness
    Steven de Jong
    Karl Tuyls
    Autonomous Agents and Multi-Agent Systems, 2011, 22 : 103 - 126
  • [7] Human-inspired computational fairness
    de Jong, Steven
    Tuyls, Karl
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2011, 22 (01) : 103 - 126
  • [8] Semantic similarity measures for Malay sentences
    Noah, Shahrul Azman
    Amruddin, Amru Yusrin
    Omar, Nazlia
    ASIAN DIGITAL LIBRARIES: LOOKING BACK 10 YEARS AND FORGING NEW FRONTIERS, PROCEEDINGS, 2007, 4822 : 117 - 126
  • [9] Measuring semantic similarity within sentences
    Liu, Xiao-Ying
    Zhou, Yi-Ming
    Zheng, Ruo-Shi
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 2558 - +
  • [10] Semantic Textual Similarity of Sentences with Emojis
    Debnath, Alok
    Pinnaparaju, Nikhil
    Shrivastava, Manish
    Varma, Vasudeva
    Augenstein, Isabelle
    WWW'20: COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2020, 2020, : 426 - 430