Name
Title | ||
|---|---|---|
Hybrid Self-Organizing Map and Neural Network Clustering Analysis for Technology Professionals Turnover Rate Forecasting |
Abstract | ||
|---|---|---|
This research applies clustering analysis technology of data mining to predict trend of the Technology Professionals turnover rate, including SUM (Self-Organizing Map) combined with Artificial Neural Network clustering analysis method. Meanwhile, this hybrid clustering method is applied to research the individual characteristics of turnover trend clusters. The turnover high peak period which is after Chinese calendar and an age bracket of high alteration circle has been consider for major research target and also used to be the transaction questionnaire. All Technology Professionals' case has been attached in Taiwan famous company. According to our research, the results show the high outstanding turnover trend circle mainly caused by non-identification of inner fidelity identification, leadership and management. The clustering accuracy rate reaches 92.7% by way of cross-verification. The application of this model, also helps rapidly prevent the problem for loss of key human-resource. Meanwhile, this will excite the organization to learn to enhance the enterprise competition ability and improve the efficiency. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14831-6_24 | ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS |
Keywords | Field | DocType |
Turnover Trend,Clustering Analysis,Self-Organizing Map,Neural Network Clustering | Turnover,Data mining,Fidelity,Computer science,Self-organizing map,Artificial intelligence,Artificial neural network,Cluster analysis,Database transaction,Machine learning | Conference |
Volume | ISSN | Citations |
93 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Sheng Lin | 1 | 0 | 0.34 |
| Chin-Yuan Fan | 2 | 473 | 28.27 |
| Fan Pei-Shu | 3 | 4 | 2.20 |
| Yen-Wen Wang | 4 | 201 | 15.59 |