- Enhanced Arabic Information Retrieval System based on Arabic Text Classification: Innovations in Information Technology, 4th International Conference on: Publication Date: 18-20 Nov. 2007
http://www.ieeexplore.ieee.org/xpl/freeabs_all.jsp?
The paper presents enhanced, effective and simple approach to text classification. The approach uses an algorithm to automatically classifying documents. The main idea of the algorithm is to select feature words from each document; those words cover all the ideas in the document. The results of this algorithm are list of the main subjects founded in the document. Also, in this paper the effects of the Arabic text classification on Information Retrieval have been investigated. The system evaluation was conducted in two cases based on precision/recall criteria: evaluate the system without using Arabic text classification and evaluate the system with Arabic text classification. A series of experiments were carried out to test the algorithm using 242 Arabic abstracts. Additionally, automatic phrase indexing was implemented. Experiments revealed that the system with text classification gives better performance than the system without text classification.
2. Experiments with the Successor Variety Algorithm Using the Cutoff and Entropy Methods: Riyad Al-Shalabi, Ghassan Kannan, Iyad Hilat, Ahmad Ababneh and Ahmad Al-Zubi : Information Technology Journal 2005.
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In the present study a system have developed that uses the Successor Variety Stemming Algorithm to findstems for Arabic words.A corpus of242 abstracts have obtained from the Saudi Arabian National Computer Conference. All of these abstracts involve computer science and information systems. The study have set out to discoverwhether the Successor Variety Stemming Algorithm technique with the Cutoff Method can be used for the Arabic Language or not. In addition, the Successor Variety Algorithmhave compared with the Cutoff and the Successor Variety with Entropy Method. Stemming is typicallyused in the hope of improving the accuracy of the searchreducing the size of the index. The results ofpresent research show that the Successor Variety Algorithm with the Cutoff Method is better than Successor Variety Algorithm with the Entropy Method. We have achieved an 84% level of correctness using the Cutoff Method, but a 64% level of correctness using the Entropy Method. These experiments were carried out using Visual Basic 6.0. |
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