Neural network framework for multilingual Web documents

The rapid growth of World Wide Web has led to a dramatic increase in accessible information. Today, people use Web for a large variety of activities including travel planning, entertainment and research. However, the tools available for collecting, organizing, and sharing web content have not kept pace with the rapid growth in information. But the major complexity arises when web documents in regional languages are displayed. Understanding the content of the document and later communication through oral or text becomes difficult. This is the area the current paper addresses. To overcome the difficulty a novel concept-based mining model is proposed and states how the knowledge is created in the minds of illiterate user. The paper first presents how letters and words which form the basis of text-based communication can be used for content. Artificial neural network training helps us to give a comparative study with statistical interpretation which was studied earlier.