Ontology driven, artificial intelligence based career planning system for individuals

With rapid technological advancements and evolving job market requirements, individual career planning has become increasingly challenging. IT professionals, career changing individuals, and NEET (Not in Employment, Education, or Training) individuals often lack the resources for effective career development and lifelong learning. This thesis proposes the development of an AI-based career planning system that leverages data science and machine learning to provide personalized career guidance. The main research problem addressed in this thesis is "How does an artificial intelligence-based career planning system, utilizing ontology, data science, and machine learning techniques, affect the career development and job alignment of information technology professionals, career changers, and NEET individuals?" The thesis employs a Design Science Research (DSR) methodology, focusing on the creation and evaluation of innovative artifacts to solve practical problems. The research follows the CRISP-DM model for data mining, encompassing phases such as business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The primary data source consists of career profiles from Professional Social Media Platforms (PSMPs). Key components include an ontology-driven conceptual model utilizing Unified Foundational Ontology (UFO) and OntoUML for accurate representation of career-related data, machine learning models to calculate job fit scores and generate skill improvement recommendations, and a functional prototype to validate the system's feasibility and functionality, focusing on IT sector positions. This thesis provides a significant contribution to the field of career planning by developing an AI-based system that addresses the dynamic needs of the labor market. It emphasizes the importance of personalized career guidance and lifelong learning, particularly for individuals in the IT sector and those seeking career transitions or re-entry into the workforce. The proposed system aligns with Turkey's strategic goals for developing a qualified workforce and supporting national initiatives in lifelong learning and human resource development. It also sets a foundation for future research and development in AI-based career planning systems.