The development of inference machine model for vocation psychology based on rough set theory

In the paper the inference machine model for vocation psychology was build and developed by a rule-based rough set theory. At first, the rough set is used to optimize the rules for career psychological identification, by which the complexity of the neural network can be avoided. Second, the features used by the questionnaires are selected for input parameters of the classifier to incorporate more human like decision-making, whereas in other works, only a few of features or different characteristic options on the questionnaire, are used as deterministic parameters. A knowledge base of the behaviour characteristics and questionnaire analysis is developed from the feedbacks of some reputed career guides. These features are extracted from the carefully designed questionnaire. A rule-based rough set decision system is developed from these features to make an inference engine for career psychological identification.