What is Resume Parsing? How Does CV/Resume Parser Work?

January 07, 2018 by dev

Topics: Recruiting, Resume Enrichment, Resume Parser, Resume Management, Resume Parsing, Social Resume Parser, Resume parsing software, Parse resumes, AI, Resume Parser API, NLP, Resume parser price, Resume parsing benefits, Best resume parser, Resume parser technology, resume parsing tools, CV parsing API, Multilingual resume parser

A Résumé parsing technology converts an unstructured form of resume data into a structured format. A CV/Resume parser analyses resume data and extracts it into machine-readable output such as XML, JSON. A resume parsing software helps store, organize, and analyze resume data automatically to find the best candidate.

What will you find in this article?

Here is a typical scenario of most organizations Sound familiar?

I am the HR Manager of a large company. On average, I receive thousands of resumes per year. It is a tough task to handle resumes manually. I heard about resume parsing technology. I was wondering what a resume parser is? And how it automatically parses resumes? I took a demo with one of the leading resume parsing software providers and triedResume parser to parse information from resumes in bulk.

What is a Resume Parser?

A Resume Parser is an AI-based software that parses resumes using NLP (Natural Language Processing). It eliminates manual data entry by extracting candidates' information intelligently and saves it in pre-designed fields.

What Does a CV/Resume Parser Do?

What is resume parser

[1] A resume parser is a compiler or interpreter that converts the unstructured data into a structured form.

[2] It is a component that automatically segregates the information into various fields and parameters like contact information, educational qualification, work experience, skills, achievements, professional certifications to quickly help you identify the most relevant resumes based on your criteria.

[3] A parser takes input in the form of a sequence of program instructions and tends to build a data structure, a "parse tree," or an abstract syntax tree.

I used RChilli's Multilingual Resume Parser, which is how it drastically transformed our hiring process.

How to Select A Resume Parser?

Keep in mind the following features while selecting a CV/resume parser :

 
resume parser feature
 
  • Parses resumes of all formats, such as PDF, doc, docx, HTML, RTF
  • Easy to integrate with your existing software
  • It contains a detailed library of taxonomies to identify candidate skills
  • Choose a multilingual resume parser that automatically identifies region and language to parse information. 
  • Allows the user to enable or disable fields from resumes as per requirement using 'configuration feature.' It helps in promoting unbiased recruitment.
  • It should extract the complete resume information in maximum data fields.
  • Creates an executive or management summary so that recruiters can evaluate a candidate by reading this summary. 
  • Uses deep learning algorithm for improved extraction and smarter identification of resume data for better search results.
  • Bulk import allows a resume/job parser to parse multiple resumes/jobs in a go.
  • Email inbox integration allows users to parse resumes/jobs from single or multiple email inboxes.
  • Option to integrate RScript plugin directly to your web page within 2 min.
  • Get the parsed data in a document template designed to bring uniformity to the presentation.

Also read: Top 7 benchmarks for comparing resume parsing technology

My team didn't have to spend time skimming through the resume. The required information was retrieved at a single click. For example, our hiring team searched for a 'Marketing Manager' who had an MBA with two years of experience. The resume parsing made it possible to simply click on the qualification and experience tab of the parser rather than going through the entire CV.

Benefits of CV/Resume Parsing API:

  • Saves Time
  • It parses resumes, extracts data, and saves into your ATS quickly in segregated fields.
  • It allows you to organize your candidate’s resumes without wasting any time.
  • Less time needed to process and select the most relevant talent who is the right fit for your organization.
  • Save employees’ time in internal referral     
  • It offers auto-filling of forms in less than 10 secs so that candidates can apply to a job post in a single click without manually filling out details.
  • It also helps to build your employer brand among candidates.
  • Easily import millions of resumes overnight
  • Fast and accurate parsing results
  • It strengthens your candidate database with qualitative data. 
  • Quickly integrate the ‘apply now’ button on your career page
  • Get resume data from emails in less than two seconds
  • Enhance search results of Solr/Elasticsearch with Taxonomies
  • Remove unconscious bias through Switch on/off fields
  • Mask resumes before sending to the recruiters
  • Improve your ROI from increased conversion rate
  • Better generalization to data and simplified approach to the data acquisition process

How Does RChilli Resume Parser Exactly Work

RChilli’s resume parser is a deep learning/AI framework that identifies complete information from resumes and enriches it through its taxonomies. It extracts candidate data from resumes in 140+ data fields through REST API.

The process converts an unstructured form of resume data into a structured format. It is a program that analyses a resume/CV created in any document format, such as doc, docx, html, pdf, rtf, and extracts into a machine-readable output such as XML, JSON format through API. 

Check how to parse resumes with the RChilli:

                      1. Upload the resume from a desktop or folder     

resume parsing software to find best fit                                

                      2. Parse resume

Resume parsing- recruiters best friend

                       3. RChilli parsing API extracts that document into 140+ fields. You need to click on the required tab to get the desired results

resume parser

Resume parsing technology

Parse resumes quickly & effortlessly

Resume parsing software

And many more…….

              4. RChilli’s resume parser stores info in your cloud database or displays JSON for the user interface

What is resume parser software

                 5. This can be sold as the add-on to existing recruitment solution

You can save much time on manual transactions of each job application and CV's received. RChilli’s friendly 24/7 available customer service makes the user experience all the better.

How RChilli's Resume Parser Can Help During COVID-19 Pandemic?

  • Speed up the process of parsing resumes even while doing remote work.
  • It seamlessly integrates with other tools.
  • It provides quick results.
  • It helps to improve candidate experience so that candidates can trust you as their future employer.
     
How Can You Turn This Pandemic into an Opportunity?

Every recruitment process has a few challenges, like slow hiring, matching the right skill to job openings, etc. It is rather tougher at the time of pandemic like COVID-19 where maintaining social distancing is crucial.

RChilli understands how HR professionals are feeling right now and recommends AI-powered intelligent solutions to fasten their recruitment process.


Who Can Use Resume Parsing Technology?

Applicant Tracking System (ATS)

Job boards

Enterprises

Staffing companies

Startups

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Curious to Know Other Interesting Facts of a Resume Parser?  

Read the following articles:

Do you want to know more about the features of a resume parser?

What more does a resume parser offer?

How can a resume parser help an ATS?

How does a resume parser provide a positive candidate experience?

How does resume parsing help in unbiased recruitment?

What's the aim behind introducing Deep Learning resume parsing module?

How to create resume parser friendly resume?

 

Know More

 

ATS, staffing agencies, Job board, career sites, enterprises, and many more usually work with resume parsing software to automate the CV/Resume database. To know more, stay tuned with RChilli's Blog.

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