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Arabic Text Categorization using k-nearest neighbour, Decision Trees (C4.5) and Rocchio Classifier: A Comparative Study


Author : Adel Hamdan Mohammad, Omar Al-Momani and Tariq Alwada’n

Pages : 477-482
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Abstract

No doubt that text classification is an important research area in information retrieval. In fact there are many researches about text classification in English language. A few researchers in general talk about text classification using Arabic data set. This research applies three well known classification algorithm. Algorithm applied are K-Nearest neighbour (K-NN), C4.5 and Rocchio algorithm. These well-known algorithms are applied on in-house collected Arabic data set. Data set used consists from 1400 documents belongs to 8 categories. Results show that precision and recall values using Rocchio classifier and K-NN are better than C4.5. This research makes a comparative study between mentioned algorithms. Also this study used a fixed number of documents for all categories of documents in training and testing phase.

Keywords: Text Categorization, k-nearest neighbour, Decision tress, C4.5, Rocchio classifier

Article published in International Journal of Current Engineering and Technology, Vol.6, No.2 (April-2016)

 

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