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A Text Mining using Web Scraping for Meaningful Insights

C. Kishor Kumar Reddy, P. R. Anisha, Gia Nhu Nguyen, Gavini Sreelatha

2021Journal of Physics Conference Series10 citationsDOIOpen Access PDF

Abstract

Abstract This research involves the usage of Machine Learning technology and Natural Language Processing (NLP) along with the Natural Language Tool-Kit (NLTK). This helps develop a logical Text Summarization tool, which uses the Extractive approach to generate an accurate and a fluent summary. The aim of this tool is to efficiently extract a concise and a coherent version, having only the main needed outline points from the long text or the input document avoiding any type of repetitions of the same text or information that has already been mentioned earlier in the text. The text to be summarized can be inherited from the web using the process of web scraping or entering the textual data manually on the platform i.e., the tool. The summarization process can be quite beneficial for the users as these long texts, needs to be shortened to help them to refer to the input quickly and understand points that might be out of their scope to understand.

Topics & Concepts

Automatic summarizationComputer scienceScope (computer science)Process (computing)Natural language processingText graphInformation retrievalNatural languagePoint (geometry)Artificial intelligenceText processingWorld Wide WebProgramming languageGeometryMathematicsAdvanced Text Analysis TechniquesTopic ModelingWeb Data Mining and Analysis
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