Open AccessA Text Mining using Web Scraping for Meaningful Insights
Author(s) -
Kishor Kumar Reddy C,
P. R. Anisha,
Như Gia Nguyễn,
G. Sreelatha
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2089/1/012048
Subject(s) - automatic summarization , computer science , scope (computer science) , process (computing) , natural language processing , text graph , information retrieval , natural language , point (geometry) , artificial intelligence , text processing , world wide web , programming language , geometry , mathematics
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.