A REVIEW ON TEXT MATCHING TECHNIQUES AND APPROACHES IN NATURAL LANGUAGE PROCESSING

Abstract

Text matching is the process of relating and locating particular text matches in raw data. Text matching is a vital element in practical operations and an essential process in several fields. It has been applied in numerous tasks, similar as textual similarity, information retrieval and question answering. For most of the text matching methods, the primary step is removing spacing, punctuation, and common phrases like ”AND”, “THE”, etc . The target of text matching is to model the relation between two input text. likewise, several dynamic ways have been introduced in this environment in order to produce ease in pattern generation from words. The process contains matching of text mining, text files, text clustering, association rule extraction, world cloud, natural language processing, and text similarity measures( knowledge- based, corpus- based, string- based, and hybrid similarities). The string- based approach makes the most conspicuous form of text mining which can be applied in different cases. In this paper, we aim to give a check on techniques used in matching two Strings and analyse the results and discuss about the advantages of one technique over the other and also discuss about the drawbacks of these techniques.