Mutually-beneficial iE-E Seeker, a Web intelligent matching using multi-dimensional case-based reasoning

This paper is attempts to propose the intelligent framework, which representing processes of humans for a Web-based prospective employer-employee seeker, namely iE-E Seeker. The mutually-beneficial concept is applied in the iE-E Seeker application using multi-dimensional case-base reasoning (CBR). The proposed system, iE-E Seeker acts as a Web intelligent matching system allows the user to obtain mutual satisfaction with the mutually beneficial matching and multi-dimension weighting. Multi-dimensional case is used to represent high-order features in this project, such as the employer features and employee features. The strength of this research is attempts to introduce an intelligent matching mechanism to replace the manual comparison and traditional exact text retrieval in the current employee-seeking-employer or employer-seeking-employee model.