A Closer Look at Arabic Text Classification
| Autor: | M. Abdeen, Sami AlBouq, Sara Shehata, Ahmed Elmahalawy |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Computer science Arabic 05 social sciences Feature selection 02 engineering and technology Data science language.human_language Support vector machine Naive Bayes classifier 0202 electrical engineering electronic engineering information engineering language 020201 artificial intelligence & image processing Social media 0509 other social sciences 050904 information & library sciences Spoken language Information explosion |
| Zdroj: | International Journal of Advanced Computer Science and Applications. 10 |
| ISSN: | 2156-5570 2158-107X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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