New real world applications of data mining and machine learning have shown that popular methods may appear to be too simple and restrictive. Mining more complex, larger and generally speaking “more difficult” data sets pose new challenges for researchers and ask for novel and more complex approaches. We organize this workshop 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)
08月23日
2017
08月26日
2017
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