ICBDA' 2020: IEEE Conference on Big Data & Analytics

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class="portlet-title"><i class="icon icon-tasks"></i> Conference Information</div> </div> <div class="portlet-content"> <div align="center"> <h5> ICBDA' 2020: IEEE Conference on Big Data & Analytics</h5> <a href="https://ieeecomputer.my/icbda2020/">https://ieeecomputer.my/icbda2020/</a> <br /> <table border="0" align="center" cellpadding="0" cellspacing="1"> <tr> <td width="150" height="25"><div align="center">Submission Date:</div></td> <td width="150"><div align="center">2020-07-31 <span class="label label-important"><small>Extended</small></span></div></td> </tr> <tr> <td width="150" height="25"><div align="center">Notification Date:</div></td> <td width="150"><div align="center">2020-08-31</div></td> </tr> <tr> <td width="150" height="25"><div align="center">Conference Date:</div></td> <td width="150"><div align="center">2020-11-17</div></td> </tr> <tr> <td width="150" height="25"><div align="center">Location:</div></td> <td width="150"><div align="center">Kota Kinabalu, Sabah, Malaysia</div></td> </tr> </table> <div class="hidden-phone" align="center"> Viewed: <span class="badge badge-success">9677</span>   Tracked: <span class="badge badge-warning">1</span>   Attend: <span class="badge badge-important">0</span> </div> </div> <br /> </div> </div> <div class="portlet" id="yw1"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-bullhorn"></i> Call For Papers</div> </div> <div class="portlet-content"> <pre>Example topics of interest includes but is not limited to the following: 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 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 Big Data Management Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data Algorithms and Systems for Big DataSearch 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 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/StreamData 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 Big Data Security, Privacy and Trust 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 Trust management in IoT and other Big Data Systems 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 Big Data Models and Algorithms Foundational Models for Big Data Algorithms and Programming Techniques for Big Data Processing Big Data Analytics and Metrics Big Data Architectures Cloud Computing Techniques for Big Data Big Data as a Service Big Data Open Platforms Big Data Management Big Data Persistence and Preservation Big Data Quality and Provenance Control Big Data Storage and Retrieval Big Data Security and Privacy Big Data System Security and Integrity Big Data Information Security Privacy Preserving Big Data Analytics Usable Security and Privacy for Big Data Quality of Big Data Services Business Intelligence Technologies and Platforms Emerging hardware and software for data analytics Infrastructure and Portals Authoring and Content Management Tools Data Analytics Models e-business and New Media Delivery and Ethical Issues in Data Analytics Future Trends and Issues Data Analytics Data Mining Infrastructure, Architecture and Tools Applications in Data Mining Innovative Models in Data Mining Statistics and Algorithms Future Trends and Issues in Data Mining Machine Learning Data Visualization Issues/opportunities in Big Data Architecture and Technologies Trends in Data Visualization Data Visualization Applications Manufacturing and Cyber-physical models Industrial Practice, ethics and governance Big Data Service Performance Evaluation Big Data Service Reliability and Availability Real-Time Big Data Services Big Data Search, Mining, and Visualization Algorithms and Systems for Big Data Search Distributed, and Peer-to-peer Search Machine learning based on Big Data Visualization Analytics for Big Data Big Data Applications Big Data for Enterprise, Government, and Society Case Studies of Big Data Value Creation Big Data for Science and Engineering Research Enabling Resources for Big Data Research Big Data Sets Big Data Application Benchmarks Survey of big data research papers and/or big data sets Special Track on Real-Time Big Data Analytics Techniques and Algorithms for Real-Time Big Data Analytics Applications and Evaluation of Real-Time Big Data Systems Special Track on Big Data/Smart Cities Big Data for Improving Resilient Infrastructures Big Data Applications such as Healthcare and Transportation</pre><div class="alert alert-warning"> Last updated by <a href="/researcher/1">Dou Sun</a> in 2020-07-04</div> </div> </div>  <div class="portlet" id="yw2"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon 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title="/conference/2830"><span>136</span><span>922</span><span>431</span><span>763</span><span>137</span><span>592</span><span>965</span><span>139</span><span>193</span><span>117</span></div> </div></div> <div class="visible-phone"> <div id="yw7" class="grid-view"> <table class="table table-hover table-striped table-bordered table-condensed"> <thead> <tr> <th id="yw7_c0">Full Name</th><th id="yw7_c1">Impact Factor</th><th id="yw7_c2">Publisher</th></tr> </thead> <tbody> <tr class="odd"> <td><a href="/journal/136">The Journal of Strategic Information Systems</a></td><td>8.700</td><td>Elsevier</td></tr> <tr class="even"> <td><a href="/journal/922">Library Hi Tech</a></td><td>3.400</td><td>Emerald</td></tr> <tr class="odd"> <td><a href="/journal/431">Journal of Internet Services and Applications</a></td><td></td><td>Springer</td></tr> <tr class="even"> <td><a href="/journal/763">Computer Physics Communications</a></td><td>7.200</td><td>Elsevier</td></tr> <tr class="odd"> <td><a href="/journal/137">Statistical Analysis and Data Mining</a></td><td> </td><td>John Wiley & Sons, Ltd</td></tr> <tr class="even"> <td><a href="/journal/592">ACM Transactions on Computation Theory</a></td><td>0.800</td><td>ACM</td></tr> <tr class="odd"> <td><a href="/journal/965">Data Science Journal</a></td><td></td><td>ICSU</td></tr> <tr class="even"> <td><a href="/journal/139">ACM Transactions on Computer-Human Interaction</a></td><td>4.800</td><td>ACM</td></tr> <tr class="odd"> <td><a href="/journal/193">Knowledge Engineering Review</a></td><td></td><td>Cambridge University Press</td></tr> <tr class="even"> <td><a href="/journal/117">International Journal of Cooperative Information Systems</a></td><td>0.500</td><td>World Scientific</td></tr> </tbody> </table><div class="keys" style="display:none" title="/conference/2830"><span>136</span><span>922</span><span>431</span><span>763</span><span>137</span><span>592</span><span>965</span><span>139</span><span>193</span><span>117</span></div> </div></div> </div> </div> <div class="portlet" id="yw8"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-eye-open"></i> Recommendation</div> </div> <div class="portlet-content"> <div align="center"> <script async src="//pagead2.googlesyndication.com/pagead/js/adsbygoogle.js"></script>  <ins class="adsbygoogle" style="display:block" data-ad-client="ca-pub-6743617430731451" data-ad-slot="1870704128" data-ad-format="autorelaxed"></ins> <script> (adsbygoogle = window.adsbygoogle || []).push({}); </script> </div> </div> </div> </div> <div class="span2 hidden-phone"> <div class="sidebar-nav"> <ul id="yw9"> <li><a href="http://www.myhuiban.com/conference/track/id/2830"><i class="icon icon-plus"></i>   Track It <span class="badge badge-warning pull-right">1</span></a></li> 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