Resumes parsing and matching with jobs
The business goal
The business goal of the project was to build a system that parses resumes and jobs and performs resume/job matching to find resumes matching specific job or jobs matching specific resumes. This system takes into account gender, age, relevant backgrounds, including past job and educational experience.
From the technical point of view, for parsing resumes and jobs the system uses a complex solution based on Apache Tika, ontologies (for skills, cities, universities and so on) and NLP-based techniques. For matching, the system uses machine learning based algorithms based on a set of different information extracted from resumes and jobs systems. The trained model system ranks custom resumes/jobs and finds top N jobs/resumes that brings together the most matches and provides a score. The system provides an interface for retraining matching models based on new or updated resumes and jobs. Also, the system provides RESTful API interface that allows to use the functionality of the system for external systems.
The results of this project are:
- a sub-system built into the HR system
- an innovative way to parse resumes and CVs based on Natural Language Processing and Machine Learning
- +25% for customer retention