Date Mining Technology In Application And Research Human Resource Management Of Company

Competitions among enterprises become more severe along with the escalating of the status of China's market economy. Competition in talents rises into the vital element of competitions among enterprises. The enterprise that owns corresponding talents will occupy the market. In order to achieve the predominance in competition, an enterprise should escalate its value, take effective management measures, enhance the strategy in human resource management, and actually realize the goal of taking talents as its foundation. In the thesis, based on the application of data mining technology and theory of the management of enterprise human resources, and theory connecting with practice, the following problems are studied with actual examples and the corresponding problem-solving measures are discussed: the classification of talent types in the human resource management of SU Group, how to prevent head draining, and evaluation of the performance assessment system. Firstly to introduce the thesis, expatiates upon the background and purpose of the study as well as the meaning, content, study method and technique road-map. Competitions among enterprises root on talent competition and how to comprehensively master and reasonably utilize human resources is the primary problem of the human resource management of contemporary enterprises. The study purpose of the thesis is using scientific quantitative analysis method to find solutions of corresponding problems. Beginning with expatiation upon theory relative to data mining technology and combining with theory relative to enterprise human resource management, the thesis use data mining technology to solve problems regarding to enterprise human resource management, such as classification of talent types, preventing head draining, and evaluation of performance assessment system. Secondly to study on thesis expatiates upon theory of data mining technology including domestic and abroad research status quo of data mining technology, principles of data mining technology, practical application of data mining, as well as basic procedure and analysis approach of data mining. The expression of "discovering knowledge from database"firstly appeared in the 11th International Associated Artificial Intelligence Conference in 1989. Domestic research in this area was firstly supported by the National Science Fund in 1993. Several methods of data mining technology can be used to solve corresponding problems and correlation analysis, classification analysis, cluster analysis, anomaly analysis, and trend analysis are discussed in the thesis. Data mining is an analysis process and its essential difference to traditional analysis method lies in mining information and discovering knowledge without definite predetermined assumptions. Information attained from data mining has three characteristics: unknown beforehand, effective, and available. Data mining technology is extensively used in finance, client relationship management, retailing, marketing, process and quality control, telecommunication, chemical pharmacy, military affairs, as well as enterprise management. Thirdly to discusses the application of data mining technology in enterprise human resource management. Firstly, theory relative to enterprise human resource management is clarified. Concepts and characteristics of human resources as well as concepts, purposes, and basic functions of enterprise human resource management are expatiated upon. According to work types, the content of enterprise human resource management can be divided into four layers: basic work, procedural work, strategic work, and pioneering work. According to its appearance, information of enterprise human resource management can be divided into two types: quantitative and qualitative. In the meantime, it can be divided into database and text files according to its attribute. Secondly, it is the further discussion on the application conditions, procedures, and ranges of data mining technology in enterprise human resource management. Application conditions refer to what business problems can be solved using data mining, and data preparation on performing data mining, and various analysis algorithms of data mining. Application procedures refer to the basic process of applying data mining, including determination of business objects, data preparation, data mining, results analysis, and knowledge assimilation. For application ranges, the thesis focuses on solving three problems about human resource management using data mining, i.e., using data miningtechnology to classify enterprise talent types, prevent head draining, and evaluate performance assessment results. The three models will be used in the study of practical examples in chapter IV. Cluster analysis is used to classify enterprise talent type. Classification of talent types can make talent selection and promotion work of an enterprise more scientific and accurate. Selection tree analysis method is used to prevent head draining of an enterprise. The method focuses on the causes of head draining of enterprise, and tries to mine the actual cause so as to propose solutions about selecting talents and retaining talents for an enterprise. To the evaluation of performance assessment system, the thesis mainly carries out correlation analysis on the existing assessment indexes of an enterprise in order to assess system of examining. At last to discuss about the actual example study of the application of data mining technology in human resource management of SU Group. Firstly, retrospection of the ten years'development course of SU Group indicates that according to management and development strategy of SU Group, its development can be divided into four periods: period performing of joint stock system reform, period of actualizing transverse all-in-one strategy, period of actualizing vertical all-in-one strategy, and period of governmental shares retreating. Secondly, modes of human resource management of SU Group in different develop periods are analyzed in detail, and the reform state of human resource management of SU Group in this process is reviewed, mainly including staffing mechanism reform, distribution system reform, talent development and cultivation mechanism reform, building up of enterprise culture, and so on. The imperfections of the modes of human resource management of SU Group are mainly: the disconnection between the human resource strategy and the enterprise development strategy, void function of human resource management in terms of contemporary human resource management, head draining—the most serious problem in human resource management, imperfections of salary distribution system, and imperfection of performance assessment system and talent selection system. The six imperfections are reduced into three problems that are solved using data mining. Thirdly, human resource information and its management status quo are analyzed and expatiated upon, base on which, imperfections are pointed out and amelioration measures for...