Title :
Application of Fuzzy Data Mining Algorithm in Performance Evaluation of Human Resource
Author_Institution :
Economic & Manage. Inst., YanTai Univ., Yantai, China
Abstract :
The assessment of human resource performance objectively, thoroughly, and reasonably is critical to choosing managerial personnel suited for organizational development. Therefore, an efficient tool should be able to deal with various employees´ data and assist managers to make decision and strategic plan. As an effect mathematic tool to deal with the vagueness and uncertainty, fuzzy data mining is considered as a highly desirable tool being applied to many application areas. In this paper we applied the fuzzy data mining technique to make the assessment and selection of human resource in enterprise. We present and justify the capabilities of fuzzy data mining technology in the evaluation of human resource in enterprise by proposing a practical model for improving the efficiency and effectiveness of human resource management. Firstly, the paper briefly explained the basic fuzzy data mining theory, and proposed the fuzzy data mining algorithm in detail. We gave process steps and the flow chart of algorithm in this part. Secondly, we used the human resource management data as illustration to implement the algorithm. We used the maximal tree to cluster the human resource. Then the raw data of human resource management is compared with each cluster and calculate the proximal values based on the equation in fuzzy data mining algorithm. At last we determined the evaluation of human resource. The whole process was easy to be completed. The results of this study indicated that the methodology was practical and feasible. It could help managers in enterprise assess performance of the human resource swiftly and effectively.
Keywords :
data mining; fuzzy set theory; human resource management; trees (mathematics); fuzzy data mining; human resource evaluation; human resource management data; maximal tree; organizational development; Application software; Clustering algorithms; Companies; Data mining; Equations; Flowcharts; Fuzzy set theory; Human resource management; Personnel; Quality management; Fuzzy Data mining; Human Resource Manageme; Performance Evaluation; Rough Set;
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
DOI :
10.1109/IFCSTA.2009.90