M. BRAHIMI Belgacem

MCA

Directory of teachers

Department

Informatics Department

Research Interests

data mining machine lerning artificial intelligence Arabic text mining

Contact Info

University of M'Sila, Algeria

Email : belkacem.brahimi@univ-msila.dz

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Recent Publications

2022

Recherche d’information

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

M. BRAHIMI Belgacem, (2022), "Recherche d’information", [national] جامعة المسيلة

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Arabic Text Mining for Used Cars and Equipments Price Prediction

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

M. BRAHIMI Belgacem, (2022), "Arabic Text Mining for Used Cars and Equipments Price Prediction", [national] Computación y Sistemas , Centro de Investigación en Computación, IPN

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2021

Improving sentiment analysis in Arabic: A combined approach

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

M. BRAHIMI Belgacem, (2021), "Improving sentiment analysis in Arabic: A combined approach", [national] Journal of King Saud University-Computer and Information Sciences , Elsevier

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2020

Improving Arabic Sentiment Classification Using a Combined Approach

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

M. BRAHIMI Belgacem, (2020), "Improving Arabic Sentiment Classification Using a Combined Approach", [national] Computación y Sistemas , Centro de Investigación en Computación, IPN

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