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DPBA 2015 : International Workshop on Data-driven and Predictive Business Analytics (DPBA 2015), coheld with EDOC 2015 | |||||||||||||||
Link: http://cs.adelaide.edu.au/~dpba2015/ | |||||||||||||||
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Call For Papers | |||||||||||||||
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 IMPORTANT DATES Submission Deadline: April 27, 2015 Acceptance Notification: June 15, 2015 Camera-ready Due: July 4, 2015 Workshop Dates: 21-22 Sept 2015 SUBMISSION Paper submissions are accepted via EasyChiar at https://easychair.org/conferences/?conf=dpba2015 All submissions should be made in PDF format and comply with the [IEEE Computer Society Conference Proceedings Format Guidelines] (http://www.computer.org/portal/web/cscps/formatting). 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. ORGANIZATION 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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