Resume Parsing

Updated 8 months ago by Romain Rouvillois

The Work and Education tabs provides the structured data parsed from a resume or a profile.

Parsing and structuring a resume correctly requires two key technologies : 

  1. Semantic Segmentation: extracting personal information, experiences, education, skills, interests, etc.

    Our algorithms leverage both Deep Computer Vision and Deep Natural Language Processing methods to get the best precision and performance, on any file format (image, pdf, text, etc.).


  2. Entities Recognition: names, email, phone, occupations, degrees, companies, schools, etc. 

    The state-of-the-art algorithms we designed and trained on millions of resumes allow us to precisely identify every element of any resume. We can then assemble these elements into a structured data frame, enabling easy readibility and efficient talent assessment.

    Accurate resume parsing is finally a reality with Riminder.


How Did We Do?