【会议征文】IEEE/WIC/ACM International Conference on Web Intelligence 2015

  • 吴家章 (虚拟经济与数据科学研究中心)
  • 创建于 2015-03-20
  • 969

Dear colleagues,

We are going to propose the following workshop at IEEE/WIC/ACM International Conference on Web Intelligence 2015. You are welcomed to submit paper to our workshop.

 

Looking forward to seeing you in Singapore this December

 

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Complex methods for data and web mining

- IEEE/WIC/ACM International Conference on Web Intelligence 2015

December 6-9, 2015 / Singapore

 

(http://wi-iat15.ntulily.org)

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Scope of the workshop:

 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:

l  Optimization methods for data or web mining and machine learning

l  Multiple criteria perspectives in data mining and learning

l  Supporting human evaluation of patterns discovered from data

l  Combined classifiers for complex learning problems

l  New methods for constructing and evaluating on-line recommendation

l  Mining “difficult” data – concerning different aspects of data difficulty (time changing, class imbalanced, partially labeled, multimedia, semi-structured or graph data)

l  Mining spatial data and images

l  Identifying the most challenging applications and key industry drivers (where both theories and applications point of views have to meet together)

 

Workshop organizers:

Yong Shi

CAS Research Center on Fictitious Economy and Data Science

E-mail: yshi@ucas.ac.cn

Lingfeng Niu

CAS Research Center on Fictitious Economy and Data Science

E-mail: niulf@ucas.ac.cn

责任编辑:吴家章

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