The Application Of Data Mining Technology In The Performance Evaluation Of Higher Vocational College Teachers

With the further development of the reform and opening-up policy and the economic society in China, modern higher vocational education has entered a new phase. Higher vocational college is an important base for training technicians and social service, and its teachers are the main force of training, researching and reforming. With the application of engagement systems in higher vocational colleges, the position engagement and performance evaluation have been the main content of human resource reform of these colleges. However, the performance evaluation of teachers is currently carried out through the simple Linear Weighting way, that is, leaders or some experts marking plus students'evaluation. The result of performance evaluation directly influences the professional ranking and salary standards of teachers. Definitely, the personnel management frustrates teachers'enthusiasm and leads to many problems such as unreasonable composition of teachers, lack of teachers and brain drain.Data mining technology is the combining technology of database and artificial intelligence, which resolved the problem of the lack of useful information with a lot of data in the development of information technology and completed conversion from the business data to information for decision-making. From some of the large human resources in the database, Data mining technology tries to find the hidden information to help decision-makers find potential link between data, which makes the composition of internal talent, talent evaluation effectively carried out.Based on modern human resource management theory, and the facts of local higher vocational colleges, this thesis analyzes the present situation and problems of human resource management of these colleges, including the construction of teacher performance evaluation system, weight and quantification, classification and selection of teachers, performance evaluation and talent quality assessment, by using data mining technology for talent evaluation of a number of personnel issues such as performance evaluation, personnel selection and classification study, and improves past algorithm. The advantages and disadvantages of different methods are analyzed comparatively.According to the result of experiments, the thesis concludes 1) the index weight from AHP reflects the true thoughts of teachers, and provides a basis for using different index weights to evaluate teachers of different ages and fields.2) linear regression solves the problem of overvaluation of teachers by different classes or the great difference for the same teacher.3) clustering algorithm provides importance references for optimum arrangement of position and talents.4) ambiguity clustering algorithm predicts the evaluation, and its accuracy rate is 69.4%.On the basis of a mature human resource management experiences and assessment methods, the thesis tries to build a reasonable, creative and fair evaluation system to provide an idea for higher vocational college personnel reform.