[DL] IEEE Big Data 2014 paper submission deadline is extended to July 13, 2014

Call For Papers cfp.2014conference at GMAIL.COM
Fri Jun 27 16:57:10 CEST 2014


We have received many reuqests to extend the paper submission deadline in
the last few days,

the organization committee has decided to extend the paper submisison
deadline to July 13.

This is a firm deadline. So if you have intension to submit a paper, don’t
miss it.





Call for Papers



2014 IEEE International Conference on Big  Data  (IEEE BigData 2014)



http://cci.drexel.edu/bigdata/bigdata2014/index.htm

October  27-30, 2014, Washington DC, USA



In recent years, “Big Data” has become a new ubiquitous term. Big Data is
transforming

science, engineering, medicine, healthcare, finance, business, and
ultimately society itself.

The IEEE Big Data has established itself as the top tier research
conference in Big Data. The

first conference IEEE Big Data 2013 (
http://cci.drexel.edu/bigdata/bigdata2013/ ) was held in

Santa Clara , CA from Oct 6-7, 2013, 259 paper submissions for the main
conference and 32

paper submissions for the industry and government program. Of those, 44
regular papers and 53

short papers were accepted, which translates into a selectivity that is
on-par with top tier

conferences. Also, there were 14 workshops associated with IEEE Big Data
2013 covering various

important topics related to various aspects of Big Data research,
development and

applications, and more than 400 participants from 40 countries attend the
4-day event.





The IEEE International Conference on Big Data 2014(IEEE BigData 2014)
continues the success of

the IEEE BigData 2013. It will provide a leading forum for disseminating
the latest research

in Big Data Research, Development, and Applications.



We solicit high-quality original research papers (including significant
work-in-progress) in

any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety,
Value and Veracity)

relevant to variety of data (scientific and engineering, social,
sensor/IoT/IoE, and

multimedia-audio, video, image, etc) that contribute to the Big Data
challenges. This includes

but is not limited to the following:





1.      Big Data Science and Foundations

a.       Novel Theoretical Models for Big Data

b.      New Computational Models for Big Data

c.       Data and Information Quality for Big Data

d.      New Data Standards



2.       Big Data Infrastructure

a.       Cloud/Grid/Stream Computing for Big Data

b.      High Performance/Parallel Computing  Platforms for Big Data

c.       Autonomic Computing and Cyber-infrastructure, System
Architectures, Design and Deployment

d.      Energy-efficient Computing for Big Data

e.      Programming Models and Environments for Cluster, Cloud, and Grid
Computing to Support Big Data

f.        Software Techniques andArchitectures in Cloud/Grid/Stream
Computing

g.       Big Data Open Platforms

h.      New Programming Models for Big Data beyond Hadoop/MapReduce, STORM

i.         Software Systems to Support Big Data Computing



3.       Big Data Management

a.       Search and Mining of variety of data including scientific and
engineering, social, sensor/IoT/IoE, and multimedia data

b.      Algorithms and Systems for Big DataSearch

c.       Distributed, and Peer-to-peer Search

d.      Big Data Search  Architectures, Scalability and Efficiency

e.      Data Acquisition, Integration, Cleaning,  and Best Practices

f.        Visualization Analytics for Big Data

g.       Computational Modeling and Data Integration

h.      Large-scale Recommendation Systems and Social Media Systems

i.         Cloud/Grid/Stream Data Mining- Big Velocity Data

j.        Link and Graph Mining

k.       Semantic-based Data Mining and Data Pre-processing

l.         Mobility and Big Data

m.    Multimedia and Multi-structured Data- Big Variety Data



4.       Big Data Search and Mining

a.       Social Web Search and Mining

b.      Web Search

c.       Algorithms and Systems for Big Data Search

d.      Distributed, and Peer-to-peer Search

e.      Big Data Search  Architectures, Scalability and Efficiency

f.        Data Acquisition, Integration, Cleaning,  and Best Practices

g.       Visualization Analytics for Big Data

h.      Computational Modeling and Data Integration

i.         Large-scale Recommendation Systems and Social Media Systems

j.        Cloud/Grid/StreamData Mining- Big Velocity Data

k.       Link and Graph Mining

l.         Semantic-based Data Mining and Data Pre-processing

m.    Mobility and Big Data

n.      Multimedia and Multi-structured Data- Big Variety Data



5.      Big Data Security & Privacy

a.       Intrusion Detection for Gigabit Networks

b.      Anomaly and APT Detection in Very Large Scale Systems

c.       High Performance Cryptography

d.      Visualizing Large Scale Security Data

e.       Threat Detection using Big Data Analytics

f.       Privacy Threats of Big Data

g.      Privacy Preserving Big Data Collection/Analytics

h.      HCI Challenges for Big Data Security & Privacy

i.        User Studies for any of the above

j.        Sociological Aspects of Big Data Privacy



6.      Big Data Applications

a.       Complex Big Data Applications  in Science, Engineering, Medicine,
Healthcare, Finance, Business, Law, Education, Transportation, Retailing,
Telecommunication

b.      Big Data Analytics in Small Business Enterprises (SMEs),

c.       Big Data Analytics in Government, Public Sector and Society in
General

d.      Real-life Case Studies of Value Creation through Big Data Analytics

e.       Big Data as a Service

f.       Big Data Industry Standards

g.   Experiences with Big Data Project Deployments



INDUSTRIAL Track

The Industrial Track solicits papers describing implementations of Big Data
solutions relevant

to industrial settings. The focus of industry track is on papers that
address the practical,

applied, or pragmatic or new research challenge issues related to the use
of Big Data in

industry. We accept full papers (up to 10 pages) and extended abstracts
(2-4 pages).



Student Travel Award

IEEE Big Data  2014 will offer 25 NSF student travel awards to student
authors (including

post-doc)  (IEEE Big Data 2013 – 17 student travel awards)







Conference Co-Chairs:

Dr. Charu Aggarwal, IBM T.J Watson Research, USA

Prof. Nick Cercone, York University, Canada

Prof. Vasant Honavar, Penn State University, USA



Program Co-Chairs:

Prof. Jimmy Lin, University of Maryland, USA

Prof. Jian Pei, Simon Fraser University, Canada



Industry and Government Program Committee Chair

Mr. Wo Chang, National Institute of Standard and Technology, USA

Dr. Raghunath Nambiar, Cisco Systems Inc, USA



BigData Steering Committee Chair:

Prof. Xiaohua Tony Hu, Drexel University, USA, thu at cis.drexel.edu



Paper Submission:

Please submit a full-length paper (upto9 page IEEE 2-column format) through
the online

submission system.

http://wi-lab.com/cyberchair/2014/bigdata14/cbc_index.php



Papers should be formatted to IEEE Computer Society Proceedings Manuscript
Formatting

Guidelines (see link to "formatting instructions" below).



Formatting Instructions

8.5" x 11" (DOC, PDF)

LaTex Formatting Macros



Important Dates:

Electronic submission of full papers: July 13, 2014

Notification of paper acceptance: Sept 1, 2014

Camera-ready of accepted papers: Sept 25, 2014

Conference: October 27-30, 2014





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