Functions, rules and models: three complementary techniques for analyzing strength data
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
Expert-Driven Validation of Rule-Based User Models in Personalization Applications
Data Mining and Knowledge Discovery
The Role of Domain Knowledge in a Large Scale Data Mining Project
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Integration of Data Mining and Hybrid Expert System
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Knowledge in Data: An Introduction to Data Mining
Discovering Knowledge in Data: An Introduction to Data Mining
Discovering Similar Patterns for Characterizing Time Series in a Medical Domain
Knowledge and Information Systems
IEEE Transactions on Knowledge and Data Engineering
Mining for Implications in Medical Data
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
A Domain Knowledge-Driven Framework for Multi-Criteria Optimization-Based Data Mining Methods
NCM '08 Proceedings of the 2008 Fourth International Conference on Networked Computing and Advanced Information Management - Volume 02
A self-learning expert system for diagnosis in traditional Chinese medicine
Expert Systems with Applications: An International Journal
A Knowledge-Based System Implementation of Intrusion Detection Rules
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
Application classification through monitoring and learning of resource consumption patterns
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Symbol extraction method and symbolic distance for analysing medical time series
ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
Artificial intelligence techniques for monitoring dangerous infections
IEEE Transactions on Information Technology in Biomedicine
Mining association rules for the quality improvement of the production process
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Proposing a Business Model in Healthcare Industry: E-Diagnosis
International Journal of Healthcare Information Systems and Informatics
Hi-index | 12.05 |
Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.