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A Cognitive Ability based Decision System for Enhancing the Industry Growth using Data Mining Techniques

Charles Savarimuthu, Lenin Jeevanantham, C. Kavitha

Abstract


This research work focuses on industry objectives like employees’ performance study based on personality and Emotional behavior. The major objective is to identify the potential of employees in the working environment. The sub objectives are analyzing the employees’ personalities and draw out the information person’s motivation, preferences, a person’s interests, identifying the emotional make-up with people and situations. Eynseck Personality Inventory (EPI) is used to classify the employees’ personality. Likert scale is used to measure the emotionality of an employee. Association rule mining is used to identify the hidden patterns among the set of attributes based on interesting measures. The multilayer perception technique helps to classify employees’ ability by applying cross-validation. This analysis can be used to improve the employees’ capability and their behavior in the working environment. This study can be used to determine the employees’ performance and helps the industry management people to improve the industry growth by identifying the various capabilities of employees and their emotionality.


Keywords


Personality traits, Emotional Quotient, Association Rule, Multi-Layer Perceptron.

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References


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