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DPBA 2015 : International Workshop on Data-driven and Predictive Business Analytics (coheld with EDOC)


When Sep 21, 2015 - Sep 22, 2015
Where Adelaide, SA, Australia
Submission Deadline Jun 22, 2015
Notification Due Aug 9, 2015
Final Version Due Aug 27, 2015

Call For Papers

International Workshop on Data-driven and Predictive Business Analytics (DPBA 2015)
in conjunction with EDOC 2015.

The contemporary enterprise features the production, integration, analysis, and utilization of Big Data, which have the 4-V characteristics: volume, velocity, variety, and veracity. While the Big data hold the promise of revolutionizing our understanding and decision-making methods towards enterprises and society, uncovering the value behind Big Data requires developing innovative decision making approaches, especially predictive approaches in various aspects, such as process configurations, resource allocations, scheduling optimizations, and collaboration patterns negotiation. Models and methods from multiple disciplines, such as data integration, data mining, statistics, business intelligence, and information systems apply to the topic. However, the impact of Big Data to business decision and corresponding analytic approaches remain an open issue.

The workshop aims at discussing the research and open issues related to the data-driven business analytic methodologies and techniques in the context of enterprise Big Data. This workshop will offer a valuable opportunity for participants to exchange opinions, share experiences, advance ideas, report recent progress, and disseminate research results on the topics related to Data-driven and predictive business analytics.

Topics of interests include, but are not limited to:

- Mining big enterprise data
- Business process analytics
- Data-intensive analytics for predictive modeling
- Data-driven decision making
- Data analytics in cloud
- Intelligent services and applications based on Big Data
- Semantics, intelligent processing and services for Big Data
- Enterprise practices and solutions for Big Data
- Data-driven prediction models and methods
- Mashup services and data integration
- Social sensing and social network services
- Efficient optimization models and solutions based on Big Data
- Reasoning over uncertain data and unreliable services
- Privacy Preserving Big Data analytics and services
- Service ranking and recommendation for Big Data
- Service modeling, delivery, deployment and evolution for Big Data
- Big Data as a Service
- Credibility of data provisioning services


Submission Deadline: June 22, 2015 (extended)
Acceptance Notification: August 9, 2015
Camera-ready Due: August 27, 2015
Workshop Dates: 21-22 Sept 2015


Paper submissions are accepted via EasyChiar at

All submissions should be made in PDF format and comply with the [IEEE Computer Society Conference Proceedings Format Guidelines] ( The page limit for full papers is 10 pages; short/position papers can be as long as 5 pages.

All workshop papers will be published in the in the form of a proceedings along with EDOC proceedings. The proceedings will be published by the IEEE Computer Society Press and be made accessible through IEEE Xplore and the IEEE Computer Society Digital Library.


General Chair
Boualem Benatallah, University of New South Wales, Australia

Program Chairs
Xianzhi Wang, University of Adelaide, Australia
Michael Sheng, University of Adelaide, Australia

Publicity Chair
Yongrui Qin, University of Adelaide, Australia

Program Committee
Anne H.H. Ngu, Texas State University, USA
Claudio A. Ardagna, University of Milan, Italy
Djamal Benslimane, Claude Bernard Lyon 1 University, France
Fanjing Meng, IBM China Research Laboratory, China
Helen Paik, University of New South Wales, Australia
Hongzhi Wang, Harbin Institute of Technology, China
Jian Yu, Auckland University of Technology, New Zealand
Jun Wei, Institue of Software, Chinese Academy of Sciences, China
Lina Yao, University of Adelaide, Australia
Muhammad Younas, Oxford Brookes University, UK
Qi Yu, Rochester Institute of Technology, USA
Sherali Zeadally, University of Kentucky, USA
Wei Tan, IBM T. J. Watson Research Center, USA
Weiping Li, Peking University, China
Xitong Li, HEC Paris, France
Xue Li, University of Queensland, Australia
Yan Wang, Macquarie University, Australia
Zakaria Maamar, Zayed University, UAE
Zhongjie Wang, Harbin Institute of Technology, China

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