Case-based reasoning and the deep structure approach to knowledge representation
ICAIL '91 Proceedings of the 3rd international conference on Artificial intelligence and law
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Change Management, a Critical Success Factor for e-Government
DEXA '01 Proceedings of the 12th International Workshop on Database and Expert Systems Applications
Massively Parallel Case-Based Reasoning with Probabilistic Similarity Metrics
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
An empirical study of predicting software faults with case-based reasoning
Software Quality Control
Minitrack: E-Government Information and Knowledge Management
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
CBR model for the intelligent management of customer support centers
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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In e-government, decision makers need support in their decision processes that may vary from simple nature to complex one. Authorities desire an intelligent workflow for their multilevel approval cycle. In this paper, we propose to use Case Base Reasoning (CBR) for the approval of small projects in public sector. CBR is an artificial intelligence technique which efficiently exploits the past experience to find solution of new problems. The CBR engine maintains a repository of past cases. On a new project approval request, the proposed inference system matches similar historical cases and suggests a solution for the new project. The proposed methodology has been evaluated on a case-base of sample projects.