The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
The process of knowledge discovery in databases
Advances in knowledge discovery and data mining
Discovering data mining: from concept to implementation
Discovering data mining: from concept to implementation
Developing Industrial Case-Based Reasoning Applications: The Inreca Methodology
Developing Industrial Case-Based Reasoning Applications: The Inreca Methodology
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
ICSC '99 Proceedings of the 5th International Computer Science Conference on Internet Applications
Optimising Data-Mining Processes: A CBR Based Experience Factory for Data Mining
ICSC '99 Proceedings of the 5th International Computer Science Conference on Internet Applications
Case-Based Reasoning Technology, From Foundations to Applications
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We introduce an integrated framework for Knowledge Discovery in Databases (KDD) and Knowledge Management and show how Knowledge Management can complement KDD. Specifically, we examine methods how to improve the knowledge intensive and weak structured process of KDD through the use of an experience factory using the method of experience packaging and case based reasoning (CBR). This paper investigates how knowledge contained in the textual components of experience packages can be used to improve the retrieval of lessons learned in KDD. We add textual CBR techniques to our CBR approach in order to improve the case retrieval mechanism of the experience factory. Our technique exploits domain-specific knowledge contained in the textual parts of the packages to find better reuse candidates of lessons learned in KDD.