Semantic Similarity of Inverse Morpheme Words Based on Word Embedding

被引:0
|
作者
Zhou, Jiaomei [1 ]
Liu, Zhiying [1 ]
机构
[1] Beijing Normal Univ, Inst Chinese Informat Proc, Beijing, Peoples R China
来源
关键词
Inverse morpheme words; Semantic similarity; Word embedding;
D O I
10.1007/978-3-031-06703-7_35
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inverse morpheme words are compound words that have the same morphemes but are arranged in the opposite order. The majority of related works on the subject have focused on a narrow investigation of dictionary definitions, with few studies based on large-scale corpora. Based on the People's Daily corpus (1946-2017), we add and delete words from a base list and then obtained a word list consisting of 668 pairs of inverse morpheme words. Furthermore, we also calculated cosine similarity by using word embedding based on the distributed representation and discovered that 76% of inverse morpheme words have a cosine similarity of 0.4 or higher, and that word formation, part-of-speech, and frequency all have an impact on semantic similarity.
引用
收藏
页码:452 / 463
页数:12
相关论文
共 50 条
  • [1] An Algorithm of Semantic Similarity Between Words Based on Word Single-meaning Embedding Model
    Li X.-T.
    You S.-J.
    Chen W.
    Zidonghua Xuebao/Acta Automatica Sinica, 2020, 46 (08): : 1654 - 1669
  • [2] Word Embedding based Textual Semantic Similarity Measure in Bengali
    Iqbal, Md Asif
    Sharif, Omar
    Hoque, Mohammed Moshiul
    Sarker, Iqbal H.
    10TH INTERNATIONAL YOUNG SCIENTISTS CONFERENCE IN COMPUTATIONAL SCIENCE (YSC2021), 2021, 193 : 92 - 101
  • [3] Morpheme Level Word Embedding
    Galinsky, Ruslan
    Kovalenko, Tatiana
    Yakovleva, Julia
    Filchenkov, Andrey
    ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE, 2018, 789 : 143 - 155
  • [4] Sentiment Analysis of Chinese Words Using Word Embedding and Sentiment Morpheme Matching
    Niu, Jianwei
    Sun, Mingsheng
    Mo, Shasha
    COLLABORATIVE COMPUTING: NETWORKING, APPLICATIONS AND WORKSHARING, COLLABORATECOM 2017, 2018, 252 : 3 - 12
  • [5] A novel model for semantic similarity measurement based on wordnet and word embedding
    Zhao, Fuqiang
    Zhu, Zhengyu
    Han, Ping
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 40 (05) : 9831 - 9842
  • [6] Combining Word Embedding and Semantic Lexicon for Chinese Word Similarity Computation
    Pei, Jiahuan
    Zhang, Cong
    Huang, Degen
    Ma, Jianjun
    NATURAL LANGUAGE UNDERSTANDING AND INTELLIGENT APPLICATIONS (NLPCC 2016), 2016, 10102 : 766 - 777
  • [7] The Semantic Similarity Relation of Entities Discovery: Using Word Embedding
    Ruan, Dong-ru
    Mao, Yu-xin
    Pan, Hong-yan
    Gao, Kai
    2017 9TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC 2017), 2017, : 845 - 850
  • [8] A survey on word embedding techniques and semantic similarity for paraphrase identification
    Kubal, Divesh R.
    Nimkar, Anant V.
    International Journal of Computational Systems Engineering, 2019, 5 (01) : 36 - 52
  • [9] Automated Short-Answer Grading using Semantic Similarity based on Word Embedding
    Lubis, Fetty Fitriyanti
    Mutaqin
    Putri, Atina
    Waskita, Dana
    Sulistyaningtyas, Tri
    Arman, Arry Akhmad
    Rosmansyah, Yusep
    INTERNATIONAL JOURNAL OF TECHNOLOGY, 2021, 12 (03) : 571 - 581
  • [10] Exploring Semantic Similarity Measure Based on Word Embedding Representation for Arabic Passages Retrieval
    Lahbari, Imane
    El Alaoui, Said Ouatik
    ADVANCED INTELLIGENT SYSTEMS FOR SUSTAINABLE DEVELOPMENT (AI2SD'2020), VOL 2, 2022, 1418 : 978 - 989