There are a lot of data mining algorithms and methodologies for various fields and various problematic. Each data mining researcher/practitioner is faced with assessing the performance of his own solution(s) in order to make comparisons with state of the art approaches. He should also describe the intrinsic quality of the discovered patterns. Which methodology, which benchmarks, which measures of performance, which tools, which measures of interest, etc., should be used, and why? Every one should answer the previous questions, and assessing the quality and the performance is a critical issue.

QIMIE'13 will focus on the theory, the techniques and the practices that can ensure the discovered knowledge is of quality. It will thus cover the problem of measuring quality of patterns, the evaluation of data mining models and the links between the discovery stage and the quality assessment stage.

QIMIE'13 is organized in association with the PAKDD'13 conference (17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Gold Coast, Australia, April 14-17, 2013), a major international conference in the areas of data mining and knowledge discovery.

Selected and revised papers will be considered for the special issue of the Journal of Intelligent Information Systems associated with the QIMIE workshop.