Name
Abstract | ||
|---|---|---|
The volume of information available on the internet, 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. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/AMS.2008.47 | Asia International Conference on Modelling and Simulation |
Keywords | Field | DocType |
fuzzy adaptive resonance theory,letter frequency,digital library,language identifications,multilingual application,incremental unsupervised learning,fuzzy art,arabic script documents,arabic script document,recent year,neural network architecture,language identification,digital libraries,unsupervised learning,natural language processing,internet,text analysis,neural network,resonance,adaptive resonance theory,resource management,frequency,neural networks | Adaptive resonance theory,Computer science,Persian,Intranet,Unsupervised learning,Urdu,Natural language processing,Language identification,Artificial intelligence,The Internet,Arabic script | Conference |
Citations | PageRank | References |
1 | 0.37 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Selamat | 1 | 717 | 77.40 |
| Choon-Ching Ng | 2 | 39 | 6.64 |