High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

Keyword Extraction using Python


Shlok Nikhil Upadhyay , Thakur Polytechnic; Praveen Shivvbachan Prajapati, Thakur Polytechnic; Abhishek Ramji Yadav, Thakur Polytechnic; Sapna Mahendra Vishwakarma, Thakur Polytechnic; Melita Fernandes, Thakur Polytechnic


Keyword, Extraction, Resume/CV, Job, Python, Registration, web-site, company, online, process, module


In the previous decade, the Information Technology sector has seen a tremendous growth with increasing popularity of the Digital World. This increasing popularity is widely visible with everything going online whether it is online shopping, online food ordering, online banking, online job search and many more. There is no doubt that the job sector has seen increased popularity with the increasing digital world. Now, these online job search facility is being provided by many different companies, some even providing the option to apply for a job online. These companies have some very well defined web-sites, mobile applications where the users can register themselves, search for jobs and apply for jobs online. In these web-sites and applications when the user registers, he has to fill the Registration form as well as upload his Resume/CV making it a time consuming process. This is where the concept of Keyword Extraction comes into the picture. The basic idea is to make the user upload his Resume/CV, extract necessary information from the Resume/CV and fill it in the registration form automatically to speed up the registration process. Now this can be achieved with any web designing programming language and its web framework. Python has been the favourite language among programmers be it a beginner or experienced due to its easy code readability and dynamic typing ability. So, Python can be used to implement this idea and increase the speed of user registration.

Other Details

Paper ID: IJSRDV7I110435
Published in: Volume : 7, Issue : 11
Publication Date: 01/02/2020
Page(s): 327-329

Article Preview

Download Article