BELGACEM Brahimi

Habib TRITRAOUI

Word Embedding for Arabic Text Classification.

Bouchareb Douâa , Soufane Wissam

Développement d'un Site Web pour L'Artisanat et L'Industrie Traditionnelle

Aicha Badza , Nour El Houda Messaoudi

Un site web pour le suivi des patients dans un établissement hospitalier

BEZZIANE Manar , BOUFESSIOU Afaf

CONCEPTION ET RÉALISATION D’UN SITE WEB POUR LA GESTION D’UN RESTAURANT

Abd Eldjebar Charif , Abd Elnasser Chenene

Fouille de textes Appliquée au Saint Coran

سلمانة محمد الأمين , بن البار محمد, بلمنور منال

موقـــــع الكتــــــروني عقــــــاري

يوسفي نور الهدى , شلابي سارة, تاهمي نور الهدى

Un site web pour le soutien psychologique

شنيح شيماء , امرو مروة, بو جملين ريحانة

Site Web pour la gestion d’un cabinet vétérinaire

Chadi Manel , Bouzidi Fatima Nour El Houda

Classification des Sentiments en langue arabe

abstract

Citation

HADJI Ayat , Belgacem Brahimi , BILAL Lounnas , WAFA Bouras , ,(2025-12-03), bloom taxonomy question classification across languages opportunities and challenges in arabic NLP,National conference on artificial intelligence - techniques and recent application,University of ziane achour djelfa

Today, companies and businessmen are increasingly interested in the web for its potential and opportunities in marketing and commercial activities. Despite the importance of Internet advertising of used equipments available on the web, work targeting their analysis is neglected. In this paper, we study the utility of using text mining techniques as well as the role of textual data in improving price prediction. In order to evaluate the proposed methods, we collected advertisements for two cases: the sale of used cars and lots of construction equipments. In addition, we applied four prediction algorithms to estimate prices of used cars and equipments. Experimental results showed that the integration of text mining techniques improves significantly predicting the price of used cars and equipments.

Citation

Belgacem Brahimi , , (2022), Arabic Text Mining for Used Cars and Equipments Price Prediction, Computación y Sistemas, Vol:26, Issue:2, pages:1015-1025, Centro de Investigación en Computación, IPN

يحتوي ملف الدروس سلسلة المحاضرات الخاصة بمقياس (Recherche d’information) السنة الثالثة ليسانس

Citation

BelgacemBrahimi , ,(2022); Recherche d’information,جامعة المسيلة,

Sentiment analysis SA is concerned with determining users’ opinions from text reviews. However, mining these opinions from massive amounts of unstructured and lengthy documents is a challenging task. In this paper, we propose methods that extract valuable opinions and values from online movie reviews to improve SA in Arabic. First, we propose a method that explores the role of n-gram and skip-n-gram models in opinion classification. Second, we study a method that exploits subjective words such as adjectives and nouns by applying Part-Of Speech tagging. Both of the methods are combined with a feature reduction technique to enhance SA results. Third, we present a method that seeks to extract relevant opinions such as review summaries and conclusion opinions. Then, a combined approach is proposed to augment opinion classification results. Forth, we introduce a method for analyzing customers’ opinions by determining factors impacting their attitudes based on the costumer value model. Experimental results conducted on two datasets prove that our proposed methods are effective and provide better scores than baseline sentiment classifiers. The best obtained classification results reached 96% in F-Measure. These results indicate also that the aesthetic factor is the most influent factor in Arabic movie reviews.

Citation

Belgacem Brahimi , , (2021), Improving sentiment analysis in Arabic: A combined approach, Journal of King Saud University-Computer and Information Sciences, Vol:33, Issue:10, pages:1242-1250, Elsevier

The aim of sentiment analysis is to automatically extract and classify a textual review as expressing a positive or negative opinion. In this paper, we study the sentiment classification problem in the Arabic language. We propose a method that attempts to extract subjective parts of document reviews. First, we select explicit opinions related to given aspects. Second, a semantic approach is used to find implicit opinions and sentiments in reviews. Third, we combine the extracted aspect opinions with the sentiment words returned by the lexical approach. Finally, a feature reduction technique is applied. To evaluate the proposed method, support vector machines (SVM) classifier is applied for the classification task on two datasets. Our results indicate that the proposed approach provides superior performance in terms of classification measures.

Citation

Belgacem Brahimi , , (2020), Improving Arabic Sentiment Classification Using a Combined Approach, Computación y Sistemas, Vol:24, Issue:4, pages:1403-1414, Centro de Investigación en Computación, IPN