Jul-26: Informal Proceedings
Mar-29: Nitesh Chawla'talk
Feb-18: Accepted papers
Jan-4: J. of Frontiers of Computer Science PAKDD WS issue
Jan-3: Longbing Cao'talk
Dec-13: Submission is open
Oct-13: QIMIE blog is open
Invited talk by Nitesh Chawla:
Evaluation Conundrum in Machine Learning/Data Mining.
Accepted papers list is available.
Due to the extension of submission date the author notifications will be sent on Feb.6, 2011. We apology for the inconvenience from the extended notification date.
Best papers will be published in Frontiers of Computer Science in China Journal, Springer.
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.
The second Quality issues, measures of interestingness and evaluation of data mining models workshop (QIMIE'11) will focus on these questions and should be of great interest for a large panel of data miners. As a whole, QIMIE'11 intend to be a forum for a community-wide discussion of these issues and to contribute to a deep cross-fertilization within a large panel of researchers/practitioners attending PAKDD'11. Thus we strongly encourage interested peoples to propose topics and main themes that should be discussed within QIMIE'11. For that purpose, we opened a blog http://quality-evaluation-data-mining-models.blogspot.com/.
Following QIMIE'09 (organized in conjunction with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, April 2009, Bangkok, Thailand), the main themes of QIMIE'11 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'11 is organized in association with the next PAKDD'11 conference (15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Shenzhen, China, May 24-27, 2011), a major international conference in the areas of data mining and knowledge discovery.
Major topics will include but are not limited to the following:
From the previous list of key topics, although not exhaustive, and from recent publications and related workshops questioning the usefulness of research in machine learning and data mining, one can identify five major themes (to be extended, all propositions are welcome):
Stéphane Lallich, ERIC, Université Lyon 2, firstname.lastname@example.org
Philippe Lenca, Lab-STICC, Telecom Bretagne, email@example.com