Pre-processing in the context of natural language resources for Hindi lessons

Abstract

Nowadays, text data in digital format of online and offline mode is increasing rapidly, it becomes difficult to manage and retrieve the text documents. Natural language processing (NLP) is highly dependent on efficient pre-processing of text documents such as archival, retrieval, query response, text summarization, machine translation, etc.This specialized area of natural language processing has led inspired researchers to do apply machine learning algorithms to automatically pre-process documents based on languages, developing methods to process documents based on their context.Under the present research paper, a pre- processing application has been proposed in the context of natural language processing. Pre-processing is an important function in text mining, natural language processing (NLP), and information retrieval (IR). However no raw text data can be worked on without pre-processing. Text pre-processing ensures optimum results when executed properly. In the field of natural language processing, text pre-processing is used to extract interesting and knowledgeable information from unstructured textual data.This
paper proposes a pre-processing application for the Hindi legal domain to provide a comprehensive and useful understanding of important linguistic processes such as normalization, tokenization, stop word removal and stemming.