The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Data preparation for data mining
Data preparation for data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Targeting customers via discovery knowledge for the insurance industry
Expert Systems with Applications: An International Journal
A job placement intervention using fuzzy approach for two-way choice
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A team formation model based on knowledge and collaboration
Expert Systems with Applications: An International Journal
Integrating induction and deduction for finding evidence of discrimination
Proceedings of the 12th International Conference on Artificial Intelligence and Law
Classification Techniques for Talent Forecasting in Human Resource Management
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
A fuzzy MCDM approach for personnel selection
Expert Systems with Applications: An International Journal
Data mining for discrimination discovery
ACM Transactions on Knowledge Discovery from Data (TKDD)
A new TOPSIS-based multi-criteria approach to personnel selection
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A fuzzy expert system (FES) tool for online personnel recruitments
International Journal of Business Information Systems
Support managers' selection using an extension of fuzzy TOPSIS
Expert Systems with Applications: An International Journal
Personnel selection using analytic network process and fuzzy data envelopment analysis approaches
Computers and Industrial Engineering
Integrating induction and deduction for finding evidence of discrimination
Artificial Intelligence and Law
Classification and prediction of academic talent using data mining techniques
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Virtual organization for open innovation: Semantic web based inter-organizational team formation
Expert Systems with Applications: An International Journal
Using data mining to improve assessment of credit worthiness via credit scoring models
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Job performance prediction in a call center using a naive Bayes classifier
Expert Systems with Applications: An International Journal
Intelligent DSS for talent management: a proposed architecture using knowledge discovery approach
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Intelligence modeling for coping strategies to reduce emergency department overcrowding in hospitals
Journal of Intelligent Manufacturing
Domain driven data mining in human resource management: A review of current research
Expert Systems with Applications: An International Journal
iHR: an online recruiting system for Xiamen Talent Service Center
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Expert Systems with Applications: An International Journal
Smart meter monitoring and data mining techniques for predicting refrigeration system performance
Expert Systems with Applications: An International Journal
| Hi-index | 12.07 |
The quality of human capital is crucial for high-tech companies to maintain competitive advantages in knowledge economy era. However, high-technology companies suffering from high turnover rates often find it hard to recruit the right talents. In addition to conventional human resource management approaches, there is an urgent need to develop effective personnel selection mechanism to find the talents who are the most suitable to their own organizations. This study aims to fill the gap by developing a data mining framework based on decision tree and association rules to generate useful rules for personnel selection. The results can provide decision rules relating personnel information with work performance and retention. An empirical study was conducted in a semiconductor company to support their hiring decision for indirect labors including engineers and managers with different job functions. The results demonstrated the practical viability of this approach. Moreover, based on discussions among domain experts and data miner, specific recruitment and human resource management strategies were created from the results.