The Application Of Case-based Reasoning For Career Choice System

CBR(Case-Based Reasoning) is one of the most distinguishing methods different from RBR(Ruled-Based Reasoning) in Artificial Intelligence. CBR can solve the problem based on past methods and experience to solve the new problem. In short, CBR has many merits such as acquiring knowledge conveniently, easy to understand, inspiring new ideas, easily acceptable. The thesis studies how to apply CBR to career choice with a wide range of meaning. It not only can help job-seekers to learn from successful people in order to make an effective choice, but also can help enterprises to quickly and easily select suitable people for their jobs.Firstly the thesis introduces the reasoning process of CBR. The working flow and corresponding techniques are discussed in detail. Then the thesis discusses the advantages and disadvantages of CBR and introduces the case-based reasoning approach in the design, diagnosis and other areas of application. After that the thesis talks about knowledge management theory and the links between the CBR process and knowledge management process.Subsequently, a large number of theories in career choice are studied including Parson's career-people matching theory, the Holland vocational aptitude theory and other researches at home and abroad. The factors affecting career choices were summarized and analyzed.The following part focuses on how to apply CBR technology to career choice according to its unique features. A complete problem-solving process is introduced, associated with the implementation of key techniques including calculation of index weight, case representation, case retrieve, case revise and case retain.Based on the studies, the thesis carries out systems analysis, and uses the C++ builder with SQL Server database to develop the software system.