From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Business information visualization
Communications of the AIS
Information visualization in data mining and knowledge discovery
A survey of visualizations for high-dimensional data mining
Information visualization in data mining and knowledge discovery
Learning UML 2.0
Information Visualization: Beyond the Horizon
Information Visualization: Beyond the Horizon
Design and evaluation of visualization support to facilitate decision trees classification
International Journal of Human-Computer Studies
Visualization of patent analysis for emerging technology
Expert Systems with Applications: An International Journal
Intelligent physician segmentation and management based on KDD approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Assisting decision making in the event-driven enterprise using wavelets
Decision Support Systems
Supplier selection: A hybrid model using DEA, decision tree and neural network
Expert Systems with Applications: An International Journal
Visualization method for customer targeting using customer map
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A combined methodology for supplier selection and performance evaluation
Expert Systems with Applications: An International Journal
Identifying new business areas using patent information: A DEA and text mining approach
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA results are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the results of basic DEA models. The paper formally shows how the results of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides DEA results which are consistent with the framework and are ready-to-analyze with data mining tools, thanks to their specially designed table-based structures. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework.