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Word Prediction and Sentence Completion

Author(s):

Jaskirat Singh Bindra , Department of Computer Science, Maharaja Agrasen Institute of Technology; Kushagr Aggarwal, Department of Computer Science, Maharaja Agrasen Institute of Technology; Niviya Dahiya, Department of Computer Science, Maharaja Agrasen Institute of Technology; Yogesh Sharma, Department of Computer Science, Maharaja Agrasen Institute of Technology

Keywords:

Natural Language Processing, N-Grams, Word Prediction, Sentence Completion

Abstract

In the field of Artificial Intelligence, on one hand, scientists have made many enhancements that helped a lot in the development of millions of smart devices. On the other hand, scientists brought a revolutionary change in the field of word processing and one of the biggest challenges in it is to identify the preceding words and actually suggest succeeding words that conform to semantic rules of the given language. One of the most widely used techniques for the validity of these types of document is Natural Language Processing. Natural Language Processing is a subfield of artificial intelligence concerned with the interactions between computers and human languages, in particular how computers process and analyze large amounts of natural language data. In this project we have based our word prediction on N-Grams model and have added the support of english grammar rules for improving the quality of the word prediction tools currently in use. By implementing separate rules for all the punctuation marks encountered in the English text we aim to improvise the word prediction at the granular level and thus as the end result obtain a sentence completion tool based purely on the limiting punctuation marks such as the "?" , "." or "!".

Other Details

Paper ID: IJSRDV7I30456
Published in: Volume : 7, Issue : 3
Publication Date: 01/06/2019
Page(s): 744-747

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