Applied Research Of Cluster Analysis In University Employment

This thesis analyzes the employment of college graduates previous methods and the development of the current graduate employment situation, and proposed classification model by constructing a professional employment, the professional guidance of the working methods of different employment ideas, and in particular the introduction of a data mining study Cluster analysis techniques employed classification as a professional model building tool.In concrete study, at first this thesis analyzed the level of clustering analysis algorithm and Kmeans algorithm and classification model in the professional building in the employment to be used, but the algorithm itself limited by the mining results obtained have a greater optimization of space. Secondly, this thesis will Kmeans AHP algorithm and each other to make up for the organic integration of algorithms, this thesis proposes a new fusion algorithm. After discuss and study, the fusion algorithm is applied to the construction of professional employment in the classification model to obtain a better classification result clustering, to the requirements needed to build models. Finally, this integrated approach in the clustering outcome of the knowledge and analysis, has been easy to accept and understand knowledge. According to knowledge representation, the paper outlines the new employment ideas, promote our university's graduates find jobs.This thesis describes the integration of specific data analysis algorithms and Kmeans algorithm level of the new algorithm, but also for the practical application of data mining technology has added a new way.