Developing web based automatic language identification and translation system

Language identification is an important task for web information retrieval services. Automatic language identification and translation have become increasingly important, as more and more documents are being served on internet within many languages. The identification problem can be seen as a specific instance of the more general problem of an item classification though its attributes. In the processes, artificial neural networks were used to identify languages in multi-lingual documents. The results have shown that the approach presented in this work is very successful to meet the expectations in real-time language identification accuracy and translate into 41 different language with the help of a developed platform. It is expected that with the support of this thesis web based documents might be used by internet users as effective as possible.