The intent of Natural Language Processing (NLP) group is to design and build software that will analyse, understand and generate languages that humans use naturally so in the due course eventually it will address the computer user as though you are addressing another person. The information era has brought us vast amounts of digitized text that is generated, propagated, exchanged, stored and accessed through the World Wide Web which is a mighty tool of communication at the present time. Internet users demand useful and reliable information from the web in the shortest time possible but it has been found that there are a number of obstacles for fulfilling this demand.

Many times you would have noticed that when you search for the information on a search engine, most of the results you get are irrelevant. Also it becomes increasingly difficult for internet users to identify useful information from the thousands of results searched by search engines. It is here that NLP comes into picture because it helps the computer to understand what the user wants. It improves the accuracy of search engine results.

But this is not as easy as it seems because when it comes to natural language, the symbol system which is the easiest for the humans to use is the toughest to master for a computer. Therefore, in order to make a machine understand a language, good programming and use of high technology is essential which enables it to operate in a better way.

There are some major projects on NLP which include machine translation. In contrast to most existing commercial MT systems, NLP pursues a data driven approach in which all translation knowledge is learned from existing bilingual text. It is also in the process to present a new paradigm of grammar correction in which large scale statistical models and web services offer writing assistance for learners of English as a second or foreign language. This service is presently available online. Recognizing textual entailment is proposed as a generic task that captures major semantic inference needs across many natural language processing applications. NLP takes this responsibility of this major task.

There has been a lot of collaborative research and projects which revolves around Natural Language Processing (NLP). The purpose of the IFPs was to encourage researchers and practitioners to discuss the most pressing needs with respect to accessing information on the web and new ideas in NLP.