Resume Parsing Definition: What is resume parsing?
Resume parsing converts free-form resume information into structured data for storage, reporting, and analysis by a computer program. Skimming manually through a resume to find the best candidates is a traditional and time-consuming process. Resume parser helps the hiring team to screen and find the best candidates from the digital resume documents.
Recruiters use the CV parsing tool to automate the hiring process and get information about the candidates, such as their experience, personal information, education details, etc.
Resume parsing tools are an integral part of most Applicant Tracking Software (ATS).
Here is how to resume parser benefits to the ATS
Find Candidates Quickly
The primary aim of resume parsing is to find the best candidates via a computer screening process. Instead of humans finding the candidates manually, the software will screen the candidates. This software is useful to find the candidates based on keywords and match them for the best positions.
Remove Bias
The other benefit of using resume parsing technology is removing bias from the hiring process. Recruiters usually make decisions based on what they know, or they go by their gut feeling. Sofware tools can give data about the candidates even before recruiters interview them. Some parsing tools also feature that did not allow hiring teams to see candidates' details such as their names, university details, and pictures to make unbiased decisions.
Save Time and Money
It is quite cumbersome for recruiters to filter the candidates from hundreds of resumes. Technology can perform the task at a rapid speed and accurately than humans. That is why a resume parser saves recruiters time to perform another task that matters the most; when you can do multiple tasks with these tools, you save money also.
Resume Parsing Techniques
A resume is best form unstructured data form, and extracting details from it is not easy for any software. Many resume parsers today use AI, NLP, and machine learning to improve the results and accuracy of the results. Humans train resume parsing tools to read different patterns the human write resumes. The best part about machine learning is that it can learn from resume structures to give better results in the future.
The Challenges of Resume Parsing
There can be various challenges in the resume parsing process, such as using different languages, excessive formatting, and different patterns or styles. Although we have a smart solution that can counter some of the problems, is it better to keep the resume simple so that computers understand it easily.
Today computers make decisions whether you get to the next level of the interview process. Do you want to parse resumes to screen better and improve your hiring process? Contact us www.candidatezip.com
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