Natural Language Question Answering

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Umma Khatuna Jannat
Supreeth S
Nirmala S Guptha
Anitha K
Shashikala N

Abstract

As the amount of information available online is growing, the need to access it becomes increasingly important and the value of natural language processing applications becomes clear. Machine translation helps us conquer language barriers that we often encounter by translating technical manuals, support content or catalog at a significantly reduced cost. The challenge with machine translation technologies is not in translating words, but in understanding the meaning of sentences to provide a true translation. In this textual analysis can be one of the important areas where future behaviours can be predicted, Extraction of the information from any user-given passage or body of text plays a major role in Data Analysis. The user is not restricted by any general genre or category of data .The system can pose the questions based on the given textual contents. For the predicted answer system can assess the correct answer. A simple reading comprehension, while there are a lot of systems that run on machine learning algorithms, most if not all of them are closed domain with training from existing wiki articles or corpora. This work is one step closer to tackling this problem and provides a true understanding between man and machine.

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