The 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'13) Hefei, Anhui, China, October 20-23, 2013


Special Session on Big Data Call for Papers

  Overview:

Recent years have witnessed the unprecedented prevalence of "Big Data". Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately, the society itself. This year IDEAL'2013 is pleased to introduce a Special Session on Big Data. We wish to encourage researcher to submit high-quality original papers (including significant work-in-progress) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity): big data science and foundations, big data infrastructure, big data management, big data searching and mining, big data privacy/security, and big data applications.

  Instructions for Authors:

Authors are invited to submit their manuscripts (in pdf format) written in English by the deadline via the EasyChair online submission system. All submissions will be refereed by experts in the field based on originality, significance, quality and clarity.

All contributions must be original, should not have been published elsewhere and must not be submitted elsewhere during the review period. Papers should not exceed 8 pages and must comply with the format of Springer LNCS/LNAI Proceedings.

Accepted papers presented at the conference will be included in the Proceedings of IDEAL 2013, to be published by Springer in its LNCS Series, which is indexed in EI. In addition, selected papers will be invited for special issues in several leading international journals in the field, including the International Journals of Neural Systems (IJNS).

  Topics of Interests:

The topics of interests include but are not limited to:

1. Big Data Science and Foundations

  • Novel Theoretical Models for Big Data
  • New Computational Models for Big Data
  • Data and Information Quality for Big Data
  • New Data Standards
2. Big Data Infrastructure
  • Cloud/Grid/Stream Computing for Big Data
  • High Performance/Parallel Computing Platforms for Big Data
  • Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
  • Energy-efficient Computing for Big Data
  • Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
  • Software Techniques and Architectures in Cloud/Grid/Stream Computing
  • Big Data Open Platforms
  • New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
  • Software Systems to Support Big Data Computing
3. Big Data Management
  • Advanced database and Web Applications
  • Novel Data Model and Databases for Emerging Hardware
  • Data Preservation
  • Data Provenance
  • Interfaces to Database Systems and Analytics Software Systems
  • Data Protection, Integrity and Privacy Standards and Policies
  • Information Integration and Heterogeneous and Multi-structured Data Integration
  • Data management for Mobile and Pervasive Computing
  • Data Management in the Social Web
  • Crowdsourcing
  • Spatiotemporal and Stream Data Management
  • Scientific Data Management
  • Workflow Optimization
  • Database Management Challenges: Architecture, Storage, User Interfaces
4. Big Data Search and Mining
  • Social Web Search and Mining
  • Web Search
  • Algorithms and Systems for Big Data Search
  • Distributed, and Peer-to-peer Search
  • Big Data Search Architectures, Scalability and Efficiency
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Visualization Analytics for Big Data
  • Computational Modeling and Data Integration
  • Large-scale Recommendation Systems and Social Media Systems
  • Cloud/Grid/Stream Data Mining- Big Velocity Data
  • Link and Graph Mining
  • Semantic-based Data Mining and Data Pre-processing
  • Mobility and Big Data
  • Multimedia and Multi-structured Data- Big Variety Data
5. Big Data Security & Privacy
  • Intrusion Detection for Gigabit Networks
  • Anomaly and APT Detection in Very Large Scale Systems
  • High Performance Cryptography
  • Visualizing Large Scale Security Data
  • Threat Detection using Big Data Analytics
  • Privacy Threats of Big Data
  • Privacy Preserving Big Data Collection/Analytics
  • HCI Challenges for Big Data Security & Privacy
  • User Studies for any of the above
  • Sociological Aspects of Big Data Privacy
6. Big Data Applications
  • Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
  • Big Data Analytics in Small Business Enterprises (SMEs)
  • Big Data Analytics in Government, Public Sector and Society in General
  • Real-life Case Studies of Value Creation through Big Data Analytics
  • Big Data as a Service
  • Big Data Industry Standards
  • Experiences with Big Data Project Deployments

Important Dates
Paper Submission Deadline:
24 May 2013
Extended to 10 June 2013
Notification of Acceptance:
5 July 2013
Extended to 12 July 2013 *
Camera-Ready Copy Due:
26 July 2013
Early Registration:
26 July 2013
Conference Presentation:
20-23 October 2013
* Notification to most accepted papers have been sent, with several still to follow shortly. Notification for Conditional Acceptance or Reject will be sent out early next week.
Submit A Paper
Session Co-Chairs
Hui Xiong
Rutgers University, USA
Wenjun Zhou
University of Tennessee, USA
PC Members
Haibin Cheng
Facebook, USA
Lian Duan
New Jersey Institute of Technology, USA
Dihua Guo
AT&T, USA
Shuguang Ji
University of Tennessee, USA
Xing Jiang
Baidu.com, China
Yiping Ke
Institute of High Performance Computing, A*STAR, Singapore
Qi Liu
University of Science and Technology of China, China
Liang Sun
Opera Solutions, USA
Sen Wu
University of Science and Technology Beijing, China
Hao Zhang
University of Tennessee, USA
Wen Zhang
Opera Solutions, USA
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