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CMDWM 2014 : Complex methods for data and web mining - 2014 WI special session


When Aug 11, 2014 - Aug 14, 2014
Where Warsaw
Submission Deadline Apr 13, 2014
Notification Due May 6, 2014
Final Version Due May 18, 2014
Categories    data mining   machine learning   web mining   optimization

Call For Papers

The session is organized within
the 2014 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2014)
11-14 August 2014 / Warsaw, Poland


New real world applications of data mining and machine learning have shown that popular methods may appear to be too simple and restrictive. Many modern automatic systems in science, engineering, medical or social fields, and in particular concerning internet, are able to collect larger data with increasing their structure. Mining more complex, larger and generally speaking “more difficult” data sets pose new challenges for researchers and ask for novel and more complex approaches.

Following the above-mentioned motivations we organize this special session where we want to promote research and discussion on more complex and advanced methods for the particularly demanding data and web mining problems. Although we welcome submissions concerning methods based on different principles, we would like also to see among them new research on using optimization techniques. The new data and web mining problems are definitely more complex than traditional ones and they could result in more difficult non-convex optimization formulations. We would like to focus interest of data mining community on various challenging issues which come up while using complex methods to deal with the difficult data mining problems.

Suggested topics include (but are not limited to) the following:
• Optimization methods for data or web mining and machine learning
• Multiple criteria perspectives in data mining and learning
• Supporting human evaluation of patterns discovered from data
• Combined classifiers for complex learning problems
• New methods for constructing and evaluating on-line recommendation
• Mining “difficult” data – concerning different aspects of data difficulty (time changing, class imbalanced, partially labeled, multimedia, semi-structured or graph data)
• Mining spatial data and images
• Identifying the most challenging applications and key industry drivers (where both theories and applications point of views have to meet together)

Session organizers

Yong Shi, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China (email
Jerzy Stefanowski, Institute of Computing Sciences, Poznan University of Technology, Poland (email
Lingfeng Niu, Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China (email


Full papers or abstracts should be formatted according to the IEEE 2-column format.
Please refer the main Web Intelligence conference page for more details

Abstracts demonstrate work in progress, particular technical result and new idea for research and could submitted later than full papers -

Selected best papers from this special session will be invited after the conference to submit as extended versions to the international journals:
Information Technology & Decision Making
Foundations of Computing and Decision Sciences

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