DR. SHILPA PARKHI

Title: Application of natural language processing in document vettingYear: 2021

Authors: Glenda Rosy Clements, Shilpa Shekhar Parkhi
Journal: Psychology and Education
Publication date: 2021
Publisher: Scopus
URL: click here

Abstract

Natural Language Processing(NLP) is a theory-motivated range of computational techniques for the automatic analysis and representation of human language. NLP enables computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part of speech tagging to machine translation. The study discusses the design and application of NLP in Document Vetting processes. Among the numerous applications of NLP, this paper discusses the application of NLP in the document vetting process. The document vetting process is seen in many fields such as legal, finance, construction and others. The document vetting in a Bank Guarantee process is taken into consideration. An in-detailed process mapping of the Bank Guarantee is discussed, where in Document Vetting takes place in the process. As time progresses, organizations contain loads of documents in their repository. An algorithm for the score calculation for a document has been developed, to retrieve the best matched document from the repository with that of the input document. The NLP module is applied in this algorithm. The NLP module designed in this study is a customizable module and hence the organizations need not procure licenses of NLP software products. We suggest the use of NLP is in this process reduces the workload of employees, thereby increasing productivity and reducing cost. This paper is useful in the areas of banking and contract management