Hybrid approach for semantic similarity calculation between Tamil words

被引:2
|
作者
Karuppaiah D. [1 ]
Durai Raj Vincent P.M. [1 ]
机构
[1] Vellore Institute of Technology, Vellore, Tamilnadu
关键词
Indo WordNet; Knowledge-based similarity; Semantic similarity; Tamil words similarity;
D O I
10.1504/IJICA.2021.113609
中图分类号
学科分类号
摘要
Semantic similarity, sometimes referred as semantic relatedness, is one of the important concepts that help in various applications that involve natural language processing. In literature, there are plenty of similarity measures to compute the relationship among words in monolingual and cross-lingual documents. They help us in understanding text, finding plagiarism, information retrieval etc. They can be categorised based on the resources used into corpus-based and knowledge-based measures. These measures are plenty for the English language. For the Tamil language, there are hardly any works in calculating the similarity between words. In this paper, we proposed a similarity finding technique that exploits the knowledge from the resources like Tamil Indo WordNet, Tamil Wikitionary and Oxford Tamil Dictionary. We have used the definitions and example sentences of each word that are available through each of these resources for similarity calculation. The proposed approach is evaluated using human evaluated Miller Charles and Rubenstein Goodenough datasets. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码:13 / 23
页数:10
相关论文
共 50 条
  • [21] Calculation of Semantic Distances Between Words: From Synonymy to Antonymy
    Vakulenko, Maksym
    JOURNAL OF QUANTITATIVE LINGUISTICS, 2019, 26 (02) : 116 - 128
  • [22] Measuring semantic similarity between words using multiple information sources
    Lei, Jingsheng
    Journal of Information and Computational Science, 2010, 7 (02): : 601 - 608
  • [23] Measuring Semantic Similarity between Words Based on Multiple Relational Information
    Duan, Jianyong
    Wu, Yuwei
    Wu, Mingli
    Wang, Hao
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2020, E103D (01) : 163 - 169
  • [24] A METHOD FOR THE COMPUTATION OF THE SEMANTIC SIMILARITY AND RELATEDNESS BETWEEN NATURAL LANGUAGE WORDS
    Anisimov, A. V.
    Marchenko, O. O.
    Kysenko, V. K.
    CYBERNETICS AND SYSTEMS ANALYSIS, 2011, 47 (04) : 515 - 522
  • [25] Similarity of fMRI Activity Patterns in Left Perirhinal Cortex Reflects Semantic Similarity between Words
    Bruffaerts, Rose
    Dupont, Patrick
    Peeters, Ronald
    De Deyne, Simon
    Storms, Gerrit
    Vandenberghe, Rik
    JOURNAL OF NEUROSCIENCE, 2013, 33 (47): : 18597 - 18607
  • [26] A Hybrid Approach for Measuring Semantic Similarity between Documents and its Application in Mining the Knowledge Repositories
    Sumathy, K. L.
    Dr Chidambaram
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (08) : 231 - 237
  • [27] Measuring semantic similarity between words using lexical knowledge and neural networks
    Li, YH
    Bandar, Z
    Mclean, D
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2002, 2002, 2412 : 111 - 116
  • [28] A Methodology for E-Content Preparation using Semantic Similarity between Words
    Gopal, U. Nanda
    2012 INTERNATIONAL CONFERENCE ON RADAR, COMMUNICATION AND COMPUTING (ICRCC), 2012, : 235 - 238
  • [29] Measuring semantic similarity between words by removing noise and redundancy in web snippets
    Xu, Zheng
    Luo, Xiangfeng
    Yu, Jie
    Xu, Weimin
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2011, 23 (18): : 2496 - 2510
  • [30] VISUAL SIMILARITY AND SEMANTIC ACTIVATION BY PICTURES AND WORDS
    SIPLE, P
    WALLS, WF
    MILLER, C
    BULLETIN OF THE PSYCHONOMIC SOCIETY, 1985, 23 (04) : 295 - 295