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The combination of conduct, emotion, motivation, and thinking is referred toas personality. To shortlist candidates more effectively, many organizationsrely on personality predictions. The firm can hire or pick the best candidatefor the desired job description by grouping applicants based on the necessarypersonality preferences. A model is created to identify applicants' personalitytypes so that employers may find qualified candidates by examining a person'sfacial expression, speech intonation, and resume. Additionally, the paperemphasises detecting the changes in employee behaviour. Employee attitudes andbehaviour towards each set of questions are being examined and analysed. Here,the K-Modes clustering method is used to predict employee well-being, includingjob pressure, the working environment, and relationships with peers, utilizingthe OCEAN Model and the CNN algorithm in the AVI-AI administrative system.Findings imply that AVIs can be used for efficient candidate screening with anAI decision agent. The study of the specific field is beyond the currentexplorations and needed to be expanded with deeper models and newconfigurations that can patch extremely complex operations.

Personality Detection of Applicants And Employees Using K-mode Algorithm And Ocean Model