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IEEE CPBG 2015 : The 1st IEEE International Workshop on Classification Problems Embedded in the Nature of Big Data


When Aug 20, 2015 - Aug 22, 2015
Where Helsinki, Finland
Submission Deadline Apr 24, 2015
Notification Due May 31, 2015
Final Version Due Jul 1, 2015
Categories    machine learning   big data   data mining   pattern recognition

Call For Papers

The 1st IEEE International Workshop on Classification Problems Embedded in the Nature of Big Data
held in conjunction with IEEE BigDataSE-15
August 20-22, 2015, Helsinki, Finland

One of the main challenges for the machine learning algorithms are problems arising from the nature of the data itself. Such problems as high dimensionality of the feature space, small availability of specific training patterns, class and feature noise, imbalanced class distribution etc. have a major negative impact on the overall predictive accuracy of pattern recognition systems. This is especially vivid in case of big data analytics, where these problems are further deepened by 3Vs (Variety, Velocity and Volume). Big data can be affected by a much higher noise or imbalance ratio than any standard dataset analysed so far in these domains. Additionally, with big data new problems arise such as analysing complex mutual dependencies among objects, high number of classes and non-stationary nature of incoming samples.

Therefore introducing new methodologies, ranging from separate data pre-processing methods to approaches embedded in the classifiers is of primary interest to the field. The aim of this workshop is to provide a forum to exchange new theoretical ideas and practical implementations in this field.

Scope and Interests

Topics of interest include, but are not limited to:

Addressing difficulties arising in analysis of big data, that are embedded in the nature of examples
New methods for imbalanced classification (pre-processing and classifier level)
Approaches for handling noise present in the data (label, feature or mixed noise)
Efficient learning techniques for classification of massive and highly dimensional data
Machine learning algorithms for tackling dynamic and evolving structures of data
One-class classification and novelty detection for big data
Semi-supervised and unsupervised classification over large datasets
Strategies for dealing with a high number of classes (multi-class and multi-label approaches) in massive collections of objects
Methods and architectures for fast and efficient processing of algorithms for handling difficult data
Applications of mentioned topics in medicine, engineering, finance and social media

Submission Instructions

Papers submitted to the workshop should be written in English conforming to the IEEE Conference Proceedings Format (8.5" x 11", Two-Column). The paper should be submitted through the workshop website. The length of the papers should not exceed 6 pages + 2 pages for over length charges.

Accepted and presented papers will be included into the IEEE Conference Proceedings published by IEEE CS CPS and submitted to IEEE Xplore and CSDL. Authors of accepted papers, or at least one of them, are requested to register and present their work at the conference, otherwise their papers will be removed from the digital libraries of IEEE CS after the conference. Distinguished papers presented at the conference, after further revision, will be recommended to special issues of reputable SCI/EI-indexed journals.

Submitting a paper to the workshop means that, if the paper is accepted, at least one author should attend the workshop and present the paper.

Please submit your papers via the Easychair system:

Workshop Funding

This Workshop will be supported by EC under FP7, Coordination and Support Action, Grant Agreement Number 316097, ENGINE European Research Centre of Network Intelligence for Innovation Enhancement.

The main goal of the project is to enhance the research potential of the ENGINE Centre, an integral part of the Wroclaw University of Technology. The idea of ENGINE – becoming a driving force for cooperation between academic researchers and other various institutions, including industrial and governmental.

We see the organization of this Workshop as an integral part of ENGINE Centre plans, as a possibility to increase the collaboration between the ENGINE Centre and external researchers and as a way of both sharing the research findings of ENGINE Centre participants and enhancing their potential by most valuable discussions with other participants of The 9th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE-15). To contribute to the success of the Workshop, the ENGINE Centre will finance the conference fee for 10 authors of the best papers accepted for this Workshop (up to 500 euro each). This will most certainly be an attractive opportunity for researches who want to disseminate their high-quality research findings and will attract valuable participants to both the Workshop and the The 9th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE-15).

Important Dates

Submission deadline: April 24, 2015
Authors notification: May 31, 2015
Camera-ready due: July 1, 2015
Registration: July 1, 2015

Program Co-Chairs

Bartosz Krawczyk, Wroclaw University of Technology, Poland
Prof. Michał Woźniak, Wroclaw University of Technology, Poland

PC Members

Robert Burduk, Wroclaw University of Technology, Poland
Bogusław Cyganek, AGH University of Science and Technology, Poland
Manuel Graña, University of the Basque Country, Spain
Konrad Jackowski, Wroclaw University of Technology, Poland
Katarzyna Wegrzyn-Wolska, ESIGETEL, France
Mohamed Medhat Gaber, Robert Gordon University, UK
Jose Antonio Saez, University of Granada, Spain
Alexander Savio, University of the Basque Country, Spain
Jerzy Stefanowski, Poznan University of Technology, Poland
Nikolaidou Mara, Harokopio University of Athens, Greece

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