Sunday, January 2, 2011

Knowledge Actionability: Evaluation and Practices, invited talk by Longbing Cao

We are pleased to announce that Prof. Longbing Cao (University of Technology Sydney, Australia) will give an invited talk at QIMIE'11:

Knowledge Actionability: Evaluation and Practices.
Actionable knowledge discovery and delivery is very demanding and challenging. It is regarded as one of grand challenges in the next-generation knowledge discovery in database (KDD) studies. Traditionally, data mining research mainly focuses and relies on developing and improving technical interestingness. This has approved not enough in the real-world enterprise data mining and emerging applications such as bioinformatics and behavior informatics. In this talk, a general evaluation framework is discussed to measure the actionability of knowledge discovered, which covers both technical and business performance evaluation. Metrics and strategies for supporting the extraction of actionable knowledge will be discussed. Practices in evaluating findings in several domains, such as actionable trading strategies in financial data mining, actionable intervention rules for social security data mining, actionable fraud detection rules for online banking risk management, will be introduced.

Monday, December 13, 2010

Submission to QIMIE'11 workshop is open

The submission website for QIMIE'11 workshop is open (December 13, 2010).

Deadline for submission is January 10, 2011.

Thursday, October 21, 2010

Major topics to be discussed

Major topics that should be discussed in this blog:

  • 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.
Contribute to this discussion and post comments in order to propose topics and main themes that should be discussed within this blog and QIMIE'11 workshop.

Philippe & Stéphane

Wednesday, October 13, 2010

Become a contributor

If you would like to contribute to this blog please send us an email or post a comment.

Wednesday, October 6, 2010

Welcome to quality-evaluation-data-mining-models blog

Hi,
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.

This blog is dedicated to discussions about such issues in data mining.

In particular, it can be an excellent forum to prepare The second Quality issues, measures of interestingness and evaluation of data mining models workshop (QIMIE'11) 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.

Regards,
Philippe & Stéphane