Résumé Parsing or CV Parsing converts unstructured resume data into a structured form to speed up the recruitment process. It extracts candidate date from resume and saves it in data fields. The output is delivered in JSON format. Apart from parsing, there are various recruitment analytics solutions such as semantic search & match and resume enrichment which help in smart talent acquisition.
Parse resumes to get the following benefits:
- Get quality talent
- Close jobs quickly
- Save time
- No manual screening of resumes
Resume Parsing software are commonly used by recruiters, applicant tracking systems and job boards to automate extraction, analysis and storage of candidate data. This eliminates the need of sorting out resumes one by one. With least manual intervention, a lot of time is saved which can be utilized in other business activities.
Resumes created in any format can be parsed, be it doc, docx, html, pdf, rtf and results are delivered in JSON format through REST API.
A detailed collection of taxonomies can help in identifying skills and expertise of a candidate easily. Users can also define their own taxonomies which can be added to the list. Here are a few examples:
- You have written job profile as ‘Java Developer’ in your job description. Resume parser will look for job alias in its taxonomy namely ‘Java engineer’, ‘Java lead’, ‘Java Software Designer’, ‘Java Software Programmer’ etc. Data is extracted from resumes having these job profile names which gives the recruiter more options to choose from.
- For a skill ‘Project management’, skills alias can be defined as ‘Planning a Project’, ‘Executing the Project’, ‘Project Management Training’, ‘Project Cycle Management’ etc. Data is extracted from resumes having these skill alias. Thus, a parser looks for a broader perspective while hiring candidates.
- Job skills are skills’ names related to a specific job. For example, skills can be defined for ‘Java Developer’ as ‘Core Java’, ‘Web Services’, ‘My SQL’, ‘Spring MVC’, ‘Struts’, ‘Maven’ etc.
For advanced features, a resume parser is followed by Semantic Search & Match and Resume Enrichment. Semantic Matching gives you the ability to find the right candidate by matching resumes with job descriptions. It searches through candidate resume and ranks resumes according to their best matching. Usually, there are four types of matching:
- Resume to Jobs
- Job to Resumes
- Resume to Resumes
- Job to Jobs
Resume Enrichment takes information from social profiles of the candidates and updates their resume with the same. Even a passive resume database can get freshness and become more productive with updated information for skills, experience, education etc. A job score is calculated based on job seeking behavior of the candidate.
A good parser offers all the above-mentioned features to simplify and streamline the hiring process.