Abstract:
Human resource department of organizations receive infinite CVs on regular basis,
making it more complex for the HR person to find the best job candidates. In fact, an
employer receives an average of 144 CVs per job opening. Usually different people
follow the different style therefore required information about the candidates is
sometimes missed or takes time to search for. It is usually observed that many people
add lot ofunnecessary details in their CV. Upon visiting the market, it has been noticed
that industries heavily depends on evaluation tools to select the most suitable applicant
for the job. In fact, many companies are turning to systems that saves time and rapidly
finds the best candidates. HR process of finding the best candidates is challenging
because ofboth sequence ofidentifying, and quality ofdetermining the candidates.
Purpose ofthis project is to provide an efficient CV extraction tool using text mining
algorithm (K-Nearest Neighbours), and also using the features of Natural Language
Processing (NLP).The main concept ofthis research based project is to create a best
way to choose the appropriate CV accurately and in speedy process by extracting the
best matching resumes. Which will allow HR department to choose the right candidate
with minimal standard process.
