A Survey of Arabic Text Classification Models

Al-Sbou, Ahed Mleih

doi:10.11591/ijece.v8i6.pp4352-4355

Cited by 12 publications

(10 citation statements)

References 14 publications

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“…A survey is an effective tool for emphasizing the value of research [52]. To answer the second research question, an online survey was sent to 60 academics, developers, and software project managers.…”

Section: Data Collection/surveymentioning

confidence: 99%

A critical success factors for software project manager in GVTs within covid-19 pandemic

2021

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The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study is trying to identify the critical success factors (CSFs) for software project manager. A literature review was conducted to identify the CSFs. Next, an online survry was conducted to rank those factors according to their propriety. An online survey was distributed among the software developers, project managers, and academicans. The statistical package for social science (SPSS) version 22 was used to analyze the data collection. Twelfth CSFs were identified in this study. Also, the findings indicated that leadership skills factor is the highest factor level ranking in this study.

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Section: Data Collection/surveymentioning

confidence: 99%

A critical success factors for software project manager in GVTs within covid-19 pandemic

2021

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“…There are several reports in the literature that claim to present a review study on Arabic text classification. As an example, the work presented in [9] claims to be survey of the Arabic text classification. The author however provided a very broad background and definition of the term and gave a brief background of the popular four techniques, i.e.…”

Section: B Machine Learning Techniquesmentioning

confidence: 99%

“…The others are called consonant letters [8]. What also distinguishes Arabic is the huge amount of vocabularies and concepts [9]. There are 28 letters in Arabic language, in addition to the Arabic hamza ‫)ء(‬ which is considered as a letter by some Arabic linguistics and it is written from right to left.…”

Section: Introductionmentioning

confidence: 99%

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A Closer Look at Arabic Text Classification

Abdeen¹,

Albouq²,

Elmahalawy³

et al. 2019

IJACSA

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The world has witnessed an information explosion in the past two decades. Electronic devices are now available in many varieties such as PCs, Laptops, book readers, mobile devices and with relatively affordable prices. This and the ubiquitous use of software applications such as social media and cloud applications, and the increasing trend towards digitalization, the amount of information on the global cloud has surged to an unprecedented level. Therefore, a dire need exists in order to mine this massively large amount of data and produce meaningful information. Text Classification is one of the known and well established data mining techniques that has been used and reported in the literature. Text classification methods include statistical and machine learning algorithms such as Naive Baysian, Support Vector Machines and others have widely been used. Many works have been reported regarding text classification of various languages including English, Chinese, Russian, and many others. Arabic is the fifth most spoken language in the world. There has been many works in the literature for Arabic text classification. However, and to the best of our knowledge, there is no recent work that presents a good, critical and comprehensive survey of the Arabic text classification for the past two decades. The aim of this paper is to present a concise and yet comprehensive review of the Arabic text classification. We have covered over 50 research papers covering the past two decades (2000 -2019). The main focus of this paper is to address the following issues: 1) The techniques reported in the literature including. 2) New Techniques. 3) Most claimed efficient technique. 4) Datasets used and which ones are most popular. 5) Which feature selection techniques are used? 6) Popular classes/categories used. 7) Effect of stemming techniques on classification results.

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“…This boom has led researchers to research and develop properties that improve results and improve efficiency. Information Retrieval (IR) is a field of computer science of great importance in our time because of the increasing volume of information [2]. This information may need to be arranged and classified so that it can be easily retrieved.…”

Section: Introductionmentioning

confidence: 99%

Improved ICHI square feature selection method for Arabic classifiers

Alshaer

Otair

Abualigah

2020

IJ-ICT

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<span>Feature selection problem is one of the main important problems in the text and data mining domain. </span><span>This paper presents a comparative study of feature selection methods for Arabic text classification. Five of the feature selection methods were selected: ICHI square, CHI square, Information Gain, Mutual Information and Wrapper. It was tested with five classification algorithms: Bayes Net, Naive Bayes, Random Forest, Decision Tree and Artificial Neural Networks. In addition, Data Collection was used in Arabic consisting of 9055 documents, which were compared by four criteria: Precision, Recall, F-measure and Time to build model. The results showed that the improved ICHI feature selection got almost all the best results in comparison with other methods.</span>

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A Survey of Arabic Text Classification Models

Cited by 12 publications

References 14 publications

A critical success factors for software project manager in GVTs within covid-19 pandemic

A critical success factors for software project manager in GVTs within covid-19 pandemic

A Closer Look at Arabic Text Classification

Improved ICHI square feature selection method for Arabic classifiers

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