A Language Framework for Measuring Semantic and Syntactic Similarity for Arabic Texts

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A3F85CGXQ" target="_blank" >RIV/00216208:11320/25:3F85CGXQ - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188898036&doi=10.1007%2fs42979-024-02691-x&partnerID=40&md5=b78c4d0c2a44025a094611d2030a6de4" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188898036&doi=10.1007%2fs42979-024-02691-x&partnerID=40&md5=b78c4d0c2a44025a094611d2030a6de4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s42979-024-02691-x" target="_blank" >10.1007/s42979-024-02691-x</a>

Result language

angličtina

Original language name

A Language Framework for Measuring Semantic and Syntactic Similarity for Arabic Texts

Original language description

A language framework for determining the similarity of two snipped texts is proposed. The edit distance concept is employed as a frame algorithm to capture syntactic and semantic similarities. In the proposed work, syntax level distances between lemma-form words are calculated, while partial edit costs are allowed to embed semantic similarity measurements. Many knowledge resources have been used, such as words’ synonyms, negation rules, and word semantic spaces. A researchable Arabic thesaurus dictionary is built in two forms, surface form and lemma form. Semantic word spaces are generated from one of the word embedding models, which represents the words in vector spaces. The algorithm is enhanced to overcome problems with different word orders between sentences by a word permutation technique that elects the best alignment of the snipped text words to yield the best matching score. The algorithm also studied the effect of negation words on textual similarity. The proposed approach was implemented to find the similarity between Arabic language texts. Results are compared with other state-of-the-art algorithms using two benchmark datasets. The experimental results show that the proposed approach achieves a higher Pearson correlation coefficient compared to other works. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

SN Computer Science

ISSN

2662-995X

e-ISSN

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Volume of the periodical

5

Issue of the periodical within the volume

4

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

1-14

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85188898036