Resume Parsing Definition

Resume parsing is a process of converting a free-format resume text, CV and social media profile into a structured data format.

Benefits of Resume Parsing

Resume parsing eliminates the need for manual data entry. It allows applicants and companies to easily create and save meaningful data.

Using the parser to structure resume data drastically impacts searching and display capabilities of an application. Resume parsing significantly improves candidate to job matching and search results.

Who uses Resume Parsers

In today’s world of Applicant Tracking Systems (ATS), Job Boards and social media, a resume parser is a component that sits between the application and a database. Résumés in all formats and of all file types go into the parser either one at a time or resume parsing in bulk and structured profile data comes out.

Afterwards, there is a number of different ways to use the structured data. Some examples include displaying the data in a nice human readable format to your customers. Recruitment agencies may remove the contact information and submit the candidate to a client for consideration.  Many companies also save the parsed data in a database. When search engines like SOLR, Lucene, Elastic Search and others index the parsed data , they will deliver precise results as the data will be searched in context. Companies also used the entire parsed context from the resume to find other resumes that are similar to that candidate and to compare the results to parsed Jobs.

How Resume Parsers and Job Parsers work together

During the process semantic analysis and rules help in creation of hierarchies (trees) of competencies and skills. This approach aids in precision of future database searches. Similarly, the same rules are used to create a set of competencies from job orders and vacancies.

HireAbility Resume Parsing

About HireAbility’s Resume and CV Parser

HireAbility’s ALEX Resume Parser uses pattern recognition, semantic analysis, and other Artificial Intelligence techniques to extract relevant résumé/CV or job/vacancy data. Generally, the output of resume and job parsing is in XML or JSON format.

The data extracted and tagged during parsing includes but is not limited to the person’s name and contact information, employment history, education, skills and competencies, publications, awards, licenses and certifications, associations, security clearances, references, citizenship, hobbies, etc. The resume parser is a context-based tool. Because of it the parser is able to structure the most unconventional resumes. Thus the resume parser practically eliminates any chance of someone searching for Oracle as a skill ending up finding candidates who work at Oracle but have no Oracle skills.

In addition, HireAbility’s ALEX resume parser creates a summary of extracted data. The summaries include such data as the 3 most relevant competencies (most used over the years), the most recent company, competencies used in the most current job, highest education level, number of years in management positions, years of experience, security level and many more.