<div dir="ltr"><div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Call for Papers</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">2014 IEEE International Conference on Big Data (IEEE BigData 2014)</span></font></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif"><a href="http://cci.drexel.edu/bigdata/bigdata2014/index.htm">http://cci.drexel.edu/bigdata/bigdata2014/index.htm</a></span></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">October 27-30, 2014, Washington DC, USA</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming </span></font></div>
<div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">science, engineering, medicine, healthcare, finance, business, and ultimately society itself. </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">The IEEE Big Data has established itself as the top tier research conference in Big Data. The </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">first conference IEEE Big Data 2013 ( <a href="http://cci.drexel.edu/bigdata/bigdata2013/">http://cci.drexel.edu/bigdata/bigdata2013/</a> ) was held in </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">Santa Clara , CA from Oct 6-7, 2013, 259 paper submissions for the main conference and 32 </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">paper submissions for the industry and government program. Of those, 44 regular papers and 53 </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">short papers were accepted, which translates into a selectivity that is on-par with top tier </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">conferences. Also, there were 14 workshops associated with IEEE Big Data 2013 covering various </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">important topics related to various aspects of Big Data research, development and </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">applications, and more than 400 participants from 40 countries attend the 4-day event.</span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">The IEEE International Conference on Big Data 2014(IEEE BigData 2014) continues the success of </span><br></div><div>
<span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">the IEEE BigData 2013. It will provide a leading forum for disseminating the latest research </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">in Big Data Research, Development, and Applications. </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">We solicit high-quality original research papers (including significant work-in-progress) in </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity) </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">relevant to variety of data (scientific and engineering, social, sensor/IoT/IoE, and </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">multimedia-audio, video, image, etc) that contribute to the Big Data challenges. This includes </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">but is not limited to the following:</span><br></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">1.<span class="" style="white-space:pre"> </span>Big Data Science and Foundations</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Novel Theoretical Models for Big Data</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>New Computational Models for Big Data </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>Data and Information Quality for Big Data</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>New Data Standards</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">2.<span class="" style="white-space:pre"> </span>Big Data Infrastructure</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Cloud/Grid/Stream Computing for Big Data </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>High Performance/Parallel Computing Platforms for Big Data</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>Autonomic Computing and Cyber-infrastructure, System Architectures, Design and </span></font><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">Deployment</span></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>Energy-efficient Computing for Big Data</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">e.<span class="" style="white-space:pre"> </span>Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support </span></font><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">Big Data </span></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">f.<span class="" style="white-space:pre"> </span>Software Techniques andArchitectures in Cloud/Grid/Stream Computing</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">g.<span class="" style="white-space:pre"> </span>Big Data Open Platforms</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">h.<span class="" style="white-space:pre"> </span>New Programming Models for Big Data beyond Hadoop/MapReduce, STORM </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">i.<span class="" style="white-space:pre"> </span>Software Systems to Support Big Data Computing</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">3.<span class="" style="white-space:pre"> </span>Big Data Management</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Search and Mining of variety of data including scientific and engineering, social, </span></font><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">sensor/IoT/IoE, and multimedia data</span></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>Algorithms and Systems for Big DataSearch</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>Distributed, and Peer-to-peer Search</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>Big Data Search Architectures, Scalability and Efficiency</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">e.<span class="" style="white-space:pre"> </span>Data Acquisition, Integration, Cleaning, and Best Practices</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">f.<span class="" style="white-space:pre"> </span>Visualization Analytics for Big Data </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">g.<span class="" style="white-space:pre"> </span>Computational Modeling and Data Integration </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">h.<span class="" style="white-space:pre"> </span>Large-scale Recommendation Systems and Social Media Systems</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">i.<span class="" style="white-space:pre"> </span>Cloud/Grid/Stream Data Mining- Big Velocity Data</span></font></div><div>
<font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">j.<span class="" style="white-space:pre"> </span>Link and Graph Mining</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">k.<span class="" style="white-space:pre"> </span>Semantic-based Data Mining and Data Pre-processing</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">l.<span class="" style="white-space:pre"> </span>Mobility and Big Data</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">m.<span class="" style="white-space:pre"> </span>Multimedia and Multi-structured Data- Big Variety Data</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">4.<span class="" style="white-space:pre"> </span>Big Data Search and Mining</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Social Web Search and Mining</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>Web Search</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>Algorithms and Systems for Big Data Search</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>Distributed, and Peer-to-peer Search</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">e.<span class="" style="white-space:pre"> </span>Big Data Search Architectures, Scalability and Efficiency</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">f.<span class="" style="white-space:pre"> </span>Data Acquisition, Integration, Cleaning, and Best Practices</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">g.<span class="" style="white-space:pre"> </span>Visualization Analytics for Big Data </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">h.<span class="" style="white-space:pre"> </span>Computational Modeling and Data Integration </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">i.<span class="" style="white-space:pre"> </span>Large-scale Recommendation Systems and Social Media Systems</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">j.<span class="" style="white-space:pre"> </span>Cloud/Grid/StreamData Mining- Big Velocity Data</span></font></div><div>
<font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">k.<span class="" style="white-space:pre"> </span>Link and Graph Mining</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">l.<span class="" style="white-space:pre"> </span>Semantic-based Data Mining and Data Pre-processing</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">m.<span class="" style="white-space:pre"> </span>Mobility and Big Data</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">n.<span class="" style="white-space:pre"> </span>Multimedia and Multi-structured Data- Big Variety Data</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">5.<span class="" style="white-space:pre"> </span>Big Data Security & Privacy</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Intrusion Detection for Gigabit Networks </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>Anomaly and APT Detection in Very Large Scale Systems</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>High Performance Cryptography </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>Visualizing Large Scale Security Data</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">e.<span class="" style="white-space:pre"> </span>Threat Detection using Big Data Analytics</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">f.<span class="" style="white-space:pre"> </span>Privacy Threats of Big Data</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">g.<span class="" style="white-space:pre"> </span>Privacy Preserving Big Data Collection/Analytics</span></font></div><div>
<font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">h.<span class="" style="white-space:pre"> </span>HCI Challenges for Big Data Security & Privacy</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">i.<span class="" style="white-space:pre"> </span>User Studies for any of the above</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">j.<span class="" style="white-space:pre"> </span>Sociological Aspects of Big Data Privacy</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">6.<span class="" style="white-space:pre"> </span>Big Data Applications</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">a.<span class="" style="white-space:pre"> </span>Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, </span></font><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">Business, Law, Education, Transportation, Retailing, Telecommunication</span></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">b.<span class="" style="white-space:pre"> </span>Big Data Analytics in Small Business Enterprises (SMEs),</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">c.<span class="" style="white-space:pre"> </span>Big Data Analytics in Government, Public Sector and Society in General</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">d.<span class="" style="white-space:pre"> </span>Real-life Case Studies of Value Creation through Big Data Analytics</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">e.<span class="" style="white-space:pre"> </span>Big Data as a Service</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">f.<span class="" style="white-space:pre"> </span>Big Data Industry Standards</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">g.<span class="" style="white-space:pre"> </span>Experiences with Big Data Project Deployments</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">INDUSTRIAL Track</span></font></div>
<div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">The Industrial Track solicits papers describing implementations of Big Data solutions relevant </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">to industrial settings. The focus of industry track is on papers that address the practical, </span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">applied, or pragmatic or new research challenge issues related to the use of Big Data in </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).</span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif"><br></span></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">Student Travel Award</span><br>
</div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">IEEE Big Data 2014 will offer as many student travel awards as possible to student authors </span><br></div><div><span style="font-size:15px;line-height:16.866666793823242px;font-family:Calibri,sans-serif">(including post-doc) (IEEE Big Data 2013 – 17 student travel awards) </span><br>
</div><div><br></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Conference Co-Chairs:</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Dr. Charu Aggarwal, IBM T.J Watson Research, USA</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Prof. Nick Cercone, York University, Canada</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Prof. Vasant Honavar, Penn State University, USA</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Program Co-Chairs:</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Prof. Jimmy Lin, University of Maryland, USA</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Prof. Jian Pei, Simon Fraser University, Canada</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Industry and Government Program Committee Chair</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Mr. Wo Chang, National Institute of Standard and Technology, USA</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Dr. Raghunath Nambiar, Cisco Systems Inc, USA</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">BigData Steering Committee Chair:</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Prof. Xiaohua Tony Hu, Drexel University, USA, <a href="mailto:thu@cis.drexel.edu">thu@cis.drexel.edu</a> </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Paper Submission:</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Please submit a full-length paper (upto9 page IEEE 2-column format) through the online </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">submission system. </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><a href="http://wi-lab.com/cyberchair/2014/bigdata14/cbc_index.php">http://wi-lab.com/cyberchair/2014/bigdata14/cbc_index.php</a></span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting </span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Guidelines (see link to "formatting instructions" below).</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br>
</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Formatting Instructions</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">8.5" x 11" (DOC, PDF) </span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">LaTex Formatting Macros</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Important Dates:</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px"><br></span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Electronic submission of full papers: July 1, 2014</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Notification of paper acceptance: Sept 1, 2014</span></font></div><div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Camera-ready of accepted papers: Sept 25, 2014</span></font></div>
<div><font face="Calibri, sans-serif"><span style="font-size:15px;line-height:16.866666793823242px">Conference: October 27-30, 2014</span></font></div><div><br></div></div><span style="font-size:11pt;line-height:16.866666793823242px;font-family:Calibri,sans-serif">To subscribe to this list, the user sends an email, with blank subject line, to </span><span style="font-size:11pt;line-height:16.866666793823242px;font-family:Calibri,sans-serif"><a href="mailto:listserv@lists.drexel.edu">listserv@lists.drexel.edu</a></span><span style="font-size:11pt;line-height:16.866666793823242px;font-family:Calibri,sans-serif"> . In the text box, the user types: subscribe BIGDATA.<br>
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