- objective measures of interest
- subjective measures of interest and quality based on human knowledge
- quality of ontologies, actionable rules
- algorithmic properties of measures of interest
- comparison of algorithm: issues with benchmarks and experiments, the need of new data sets which match new problems, methodologies, statistical tests, etc.
- robustness evaluation and statistical evaluation
- graphical tools like ROC, cost curves
- special issues: imbalanced data, very large data, very high dimensional data, changing environments, lack of training data, graph data, etc.
- special issues in specialized domains: bio-informatics, security, information retrieval, sequential and time series data, social networks, etc.
Philippe & Stéphane