DEVELOPMENT OF SYSTEM OF PERSONALIZED RECOMMENDATIONS FOR IT STAFF RECRUITMENT: AN ONTOLOGICAL APPROACH

Abstract

Currently, the IT specialist market is characterized by a highly dynamic environment characterized by changes and the development of new IT technologies, programming languages, frameworks, etc. In this environment, an effective IT recruitment process is becoming a crucial factor in the success of any company in general, and IT companies in particular. All companies impose appropriate requirements on IT specialists in terms of their professional competencies. 
This paper examines the problem of IT personnel recruitment using currently available job search platforms in the context of the constant development and change of IT technologies. These platforms have certain limitations in their ability to search for IT specialists using keywords, due to the presence of synonyms and the inability to account for real connections between candidate competencies and the corresponding employer requirements. To address these limitations, this paper proposes a personalized recommendation system for IT specialists. This system uses an ontological approach to formalize and understand the semantics of candidate resumes and information about their professional competencies. 
The system integrates an intelligent agent for deeper linguistic (context-aware) analysis of candidate resumes and job postings, even though the text is unstructured. This approach improves the accuracy of matching candidate competency texts with the competencies noted by employers in the job posting. The proposed approach will offer candidates informed personalized job posting recommendations with career development advice and simplify the search for employees who meet employer requirements for the relevant job posting.