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|Title||Arabic text classification using decision trees|
Text mining draw more and more attention recently, it has been applied on different domains including web mining, opinion mining, and sentiment analysis. Text pre-processing is an important stage in text mining. The major obstacle in text mining is the very high dimensionality and the large size of text data. Natural language processing and morphological tools can be employed to reduce dimensionality and size of text data. In addition, there are many term weighting schemes available in the literature that may be used to enhance text representation as feature vector. In this paper, we study the impact of text pre-processing and different term weighting schemes on Arabic text classification. In addition, develop new combinations of term weighting schemes to be applied on Arabic text for classification purposes.
|Published in||Proceedings of the 12th international workshop on computer science and information technologies CSIT|
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