William Raynaut

Consistency-Based Reliability Assessment

This paper addresses the question of assessing the relative reliability of unknown information sources. We propose to consider a phase during which the consistency of information they report is analysed, whether it is the consistency of each single report, or the consistency of a report w.r.t. some trusted knowledge or the consistency of different reports together. We adopt an axiomatic approach by first giving postulates which characterize how the resulting reliability preorder should be; then we define a family of operators for building this preorder and demonstrate that it satisfies the proposed postulates.

Meta-mining Evaluation Framework: A Large Scale Proof of Concept on Meta-learning

This paper aims to provide a unified framework for the evaluation and comparison of the many emergent meta-mining techniques. This framework is illustrated on the case study of the meta-learning problem in a large scale experiment. The results of this experiment are then explored through hypothesis testing in order to provide insight regarding the performance of the different meta-learning schemes, advertising the potential of our approach regarding meta-level knowledge discovery.