ICARE: Intelligent Cognitive Assessment and Review Engine

ICARE: Intelligent Cognitive Assessment and Review Engine

Prof. Mrunalinee Soliv (mrunal1041@gmail.com),

Raunak Kambli (Raunakkambli@gmail.com), Devansh Jadhav (devansh22@gmail.com), MCT’s Rajiv Gandhi Institute of Technology, Mumbai – 400053

Abstract—

The recruitment process often faces persistent challenges with inefficiencies given multiple role-specific assessments in a single hiring cycle. This paper introduces the Intelligent Cognitive Assessment and Review Engine (ICARE), an AI-powered system that accelerates recruitment by incorporating the Adaptive Role Matching System (ARMS). ARMS produces adaptive tests targeted to role-specific demands by drawing real-time data from candidates’ responses and skills and modifying them according to the roles. This approach allows for more accurate evaluations, less redundancy, and a customized assessment process. ICARE implements refinement iterations through the spiral model, probabilistic algorithms, and graph neural net- works (GNNs) for optimal skill-to-role matching. GNNs consistently update predictions, in addition to a feedback loop with a learning mechanism that includes the input of recruiters, thus making the system more accurate over time.

Keywords—

Recruitment process, Role specific assessment, Adaptive Role matching System(ARMS), Spiral model, feedback loop, Accurate evaluation, Recruiter Input, Candidate response analysis.