Types of Parsers and How They Work
Are you considering investing in resume parsing software for your business? Are you wondering what the best parser might be and how parsing technology works?
Do you know the difference between a keyword-based parser, a grammar-based parser and a statistical parser? Not all parsers work in the same way, nor do they have the same accuracy rates.
Automation in the recruitment industry has soared. Everyone in recruiting and staffing has embraced automation technology in some form, hoping to increase efficiencies and ultimately to make more placements.
To find the most relevant candidates, the best place for most recruiters to start is by searching resumes. Accurate resume parsing is a large part of sourcing, since your recruiters can only find the right candidates if their information has been loaded correctly in your database.
Before you make a decision on selecting recruitment database software or an integrated resume parser, it can be useful to know what a resume parser is, how it works and its accuracy rates.
To learn more about the technology behind the different types of parsing technology, download this DaXtra white paper. It covers everything from identifiers to accuracy rates.
- What are the different approaches to parsing?
- What is a parser looking for?
- What is the accuracy rate of a parser?
The right resume parser can automatically load candidate and job information into your database, eliminating manual error and saving your recruiters time and effort. Resume and job parsers are an important step in increasing recruitment productivity and helping to remove human bias.
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