Natural Language Processing of Resumes

Matching potential employees to employment opportunities is a challenging task, which has significant commercial value. Employment agencies, departments in companies concerned with human resources and small company owners frequently have to read, or process, numerous resumes before identifying a short list of candidates. Working with Talent Technology, a developer of recruitment and hiring software and component technology, the intern will develop solutions in several areas of automated resume processing. The proposed project will investigate how an integration of statistical machine learning and rule based techniques from the area of natural language processing can be used to automate the resume processing task, and result in better matching and ranking of candidates for particular job descriptions. The research aims to provide algorithms, methodology and software for the rapid processing of large volumes of resumes.

Zhongmin Shi
Faculty Supervisor: 
Dr. Fred Popowich
British Columbia