{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T07:11:51Z","timestamp":1766301111417,"version":"build-2065373602"},"reference-count":65,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"LIESMARS Special Research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>We propose a novel text classification model, which aims to improve the performance of Arabic text classification using machine learning techniques. One of the effective solutions in Arabic text classification is to find the suitable feature selection method with an optimal number of features alongside the classifier. Although several text classification methods have been proposed for the Arabic language using different techniques, such as feature selection methods, an ensemble of classifiers, and discriminative features, choosing the optimal method becomes an NP-hard problem considering the huge search space. Therefore, we propose a method, called Optimal Configuration Determination for Arabic text Classification (OCATC), which utilized the Particle Swarm Optimization (PSO) algorithm to find the optimal solution (configuration) from this space. The proposed OCATC method extracts and converts the features from the textual documents into a numerical vector using the Term Frequency-Inverse Document Frequency (TF\u2013IDF) approach. Finally, the PSO selects the best architecture from a set of classifiers to feature selection methods with an optimal number of features. Extensive experiments were carried out to evaluate the performance of the OCATC method using six datasets, including five publicly available datasets and our proposed dataset. The results obtained demonstrate the superiority of OCATC over individual classifiers and other state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/fi14070194","type":"journal-article","created":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T22:31:14Z","timestamp":1656369074000},"page":"194","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Novel Text Classification Technique Using Improved Particle Swarm Optimization: A Case Study of Arabic Language"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8770-1584","authenticated-orcid":false,"given":"Yousif A.","family":"Alhaj","sequence":"first","affiliation":[{"name":"Sanaa Community College, Sanaa 5695, Yemen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelghani","family":"Dahou","sequence":"additional","affiliation":[{"name":"Mathematics and Computer Science Department, Ahmed Draia University, Adrar 01000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6956-7641","authenticated-orcid":false,"given":"Mohammed A. A.","family":"Al-qaness","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Faculty of Engineering, Sana\u2019a University, Sana\u2019a 12544, Yemen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Middle East University, Amman 11831, Jordan"},{"name":"Faculty of Computer Sciences and Informatics, Amman Arab University, Amman 11953, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9982-1321","authenticated-orcid":false,"given":"Aaqif Afzaal","family":"Abbasi","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Foundation University Islamabad, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nasser Ahmed Obad","family":"Almaweri","sequence":"additional","affiliation":[{"name":"Sanaa Community College, Sanaa 5695, Yemen"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7682-6269","authenticated-orcid":false,"given":"Mohamed Abd","family":"Elaziz","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Engineering, Galala University, Suez 435611, Egypt"},{"name":"Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates"},{"name":"Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9990-1084","authenticated-orcid":false,"given":"Robertas\u00a0","family":"Dama\u0161evi\u010dius","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102121","DOI":"10.1016\/j.ipm.2019.102121","article-title":"Arabic text classification using deep learning models","volume":"57","author":"Elnagar","year":"2020","journal-title":"Inf. Process. 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