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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Selamat, A. Ng Choon Ching |
| Copyright Year | 2008 |
| Description | Author affiliation: Fac. of Comput. Sci. & Inf. Syst., Univ. Technologi Malaysia, Kuching (Selamat, A.; Ng Choon Ching) |
| Abstract | The volume of information available on the internet, intranet, digital libraries and newsgroup has increased dramatically in recent years. Therefore, there is a growing interest in helping user better find, filter, and manage these resources. Language identification is the first step of understanding text documents which is written in. It is usually a module within multilingual application. In this paper, we introduce language identification of Arabic script documents by letter frequency. Technique used for identification is fuzzy adaptive resonance theory (ART), which is belong to the neural network architectures that perform incremental unsupervised learning. Arabic script documents such as Arabic, Persian and Urdu were used for performing language identification. From the experiments, we have found that fuzzy ART is particularly promising in terms of accuracy on language identification. |
| Starting Page | 528 |
| Ending Page | 533 |
| File Size | 195390 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769531366 |
| DOI | 10.1109/AMS.2008.47 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-13 |
| Publisher Place | Malaysia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Subspace constraints Arabic script documents Information filtering Software libraries Fuzzy ART Neural networks language identification Information filters Frequency Fuzzy neural networks Resonance Internet Resource management adaptive resonance theory (ART) |
| Content Type | Text |
| Resource Type | Article |
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