Paper Key : IRJ************578
Author: Harshwardhan Songirkar,Ankita Pandey,Tanishka Joshi,Husain Attar
Date Published: 02 May 2024
Abstract
In today's data-rich environment, the integration of natural language processing (NLP) withvisual analysis has become increasingly important to extract useful insights from complexdatasets. This study presents the development of a novel visual analysis tool driven by a stateof-the-art NLP model. The program aims to enhance the interpretability and accessibility ofdata by combining textual analysis with user-friendly graphic representations. Thismethodology makes use of contemporary NLP techniques like deep learning architectures, pretrained language models, and semantic analysis algorithms.These components enable the tool to efficiently understand unstructured textual data,including evaluations from customers, news articles, research papers, and information fromsocial media. Furthermore, interactive dashboards, graphs, and charts are part of the tool'svisual analysis component, which presents the processed textual data in an intelligible manner.Using data visualization concepts, the program allows users to analyze and assess patterns,trends, and correlations in the data. Processing Textual Data: This is one of the main featuresof the program that was designed. The NLP model uses tokenization, parsing, and extraction toextract important information from textual sources, including topic modeling, entityrecognition, sentiment analysis, and other important data. Visual Representation: Using avariety of visualization techniques, the application turns textual concepts into graphicalrepresentations that facilitate understanding and interpretation.