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

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Abstract

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.

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Authors and Affiliations

  1. Information Systems Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha, 13511, Egypt

    Shimaa Ismail & Tarek Elshishtawy

  2. Computer Systems Department, Faculty of Engineering Shoubra, Benha University, Benha, Egypt

    AbdelWahab Alsammak

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  1. Shimaa Ismail
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  2. AbdelWahab Alsammak
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  3. Tarek Elshishtawy
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Ismail, S., Alsammak, A. & Elshishtawy, T. A Language Framework for Measuring Semantic and Syntactic Similarity for Arabic Texts. SN COMPUT. SCI. 5, 351 (2024). https://doi.org/10.1007/s42979-024-02691-x

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