Open AccessWeb Scrapping: Data Extraction from Websites
Author(s) -
Iqtibas Salim Hilal Almaqbali,
Fatmah Mohammed Ali Al Khufairi,
Mohamed Samiulla Khan,
Anjum Zameer Bhat,
Ahmed Imran
Publication year - 2020
Publication title -
journal of student research
Language(s) - English
Resource type - Journals
ISSN - 2167-1907
DOI - 10.47611/jsr.vi.942
Subject(s) - computer science , world wide web , python (programming language) , web application , web development , the internet , web standards , data extraction , web page , data web , web modeling , task (project management) , programming language , engineering , medline , systems engineering , political science , law
Data is very important nowadays for almost all organizations for their existence as well as for their growth. The Internet has become the major source of data for individuals and almost all organizations. Authentic Websites are a major source of reliable data for many individuals and organizations. Extracting Data from websites is commonly referred as Web Scrapping, which refers to both manual and automated process. Extracting large amount of meaning full data from the websites manually is very difficult, tedious and redundant task. Automated Scrapping is done by writing specific programs to extract the required data from the websites. These programs are usually called as web scrappers. Web scrappers are written using many programming languages like Python, Node.js, Ruby, C++, PHP etc. Each language has its own unique features and built in libraries for performing data extraction. There are many web scrapping tools like Beautiful Soup, Octoparse, Parsehub etc. In this article we are going to analyses few recent Web Scrappers tools used in scrapping the Web.