基于人才认知的数据挖掘研究

【作者】 朱红；

【导师】 王清心； 胡建华；

【作者基本信息】 昆明理工大学 ， 计算机应用技术， 2002， 硕士

【摘要】 随着计算机技术，特别是数据库技术的发展，在人才市场上积累了大量的人才数据。如何发现隐含在这些数据中的规则和知识，并辅助决策，成了亟待解决的问题。数据挖掘技术的出现和发展为此提供了有力支持。 数据挖掘就是从大量的、不完备的数据中，提取出事先未知的、但具有价值的信息和知识的过程。本文在对数据挖掘技术的理论研究基础上，描述了该技术在人才认知系统中的应用。主要阐明了人才认知系统在数据预处理的前提下，如何运用改进的聚类方法，对人才库进行合理、高效的聚类，然后在其结果簇上进行回归分析，从而得到各类人才能力的评价标准。其中，改进的聚类算法，在聚类的合理性、高效性和精确性等方面都有显著的提高。更多还原

【Abstract】 With the development of the computer technology, especially the database technology, lots of talents data have been accumulated in the talents markets. How to discover the rules and knowledge hiding in these data so as to provide the assistant decision support has become an urgent problem to be solved. The appearance and development of the Data Mining technology has provided powerful support to this need.Data Mining is the period of picking up unknown, but valuable information and knowledge from large amount of incomplete data. Based on the theoretical research of Data Mining technology, the application of data mining technology in the talents cognition system was stated in this paper. On the basis of the pretreatment of data, exert the improved method of the clustering analysis to obtain more reasonable and high efficiency result of classification. Then on the basis of the clustering analysis, the initial regression analysis of talents data has been made and qualitative analysis result of the talents abilities has been obtained. The clustering algorithm of improvement has raising of notable at the aspect of reasonable, high efficiency and accurate nature of clustering.更多还原