Arabic script documents language identifications using fuzzy ART - Selamat, Ali (IEEE, 2008)
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.