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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ghwanmeh, S. Kanaan, G. Al-Shalabi, R. Ababneh, A. |
| Copyright Year | 2007 |
| Description | Author affiliation: Yarmouk Univ., Irbid (Ghwanmeh, S.) |
| Abstract | 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. |
| Starting Page | 461 |
| Ending Page | 465 |
| File Size | 2414162 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424418404 |
| DOI | 10.1109/IIT.2007.4430469 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-11-18 |
| Publisher Place | Dubai |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Animals Text categorization Prototypes Web pages Banking Abstracts Information retrieval Particle measurements Testing Indexing |
| Content Type | Text |
| Resource Type | Article |
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