Submissions presenting current research work on both theoretical and practical aspects of Big Data, Knowledge Discovery are encouraged. Submissions on industrial applications and experiences are also highly encouraged.<br>Track 1 – Research:<br>Big Data Query Languages and Optimization<br>Big Data Analytics and User Interfaces<br>Big Data Indexing and Storing<br>Big Data Analytics: algorithms, techniques, and systems<br>Big Data Quality and Provenance Control<br>Social Networking Data Graph Management<br>Graph mining, analysis, and querying.<br>Visualization Analytics for Big Data<br>Big Data Searching and Discovery<br>Big Data Management for Mobile Applications<br>Scalability and Parallelization using Mapreduce and beyond<br>Analytics for the Cloud Infrastructure<br>Analytics for Unstructured, Semi–structured, and Structured Data<br>Semantic for Big Data Intelligence<br>Analytics for Temporal, Spatial, Spatio–temporal, and Mobile Data<br>Analytics for Data Streams and Sensor Data<br>Analytics for Big Multimedia Data<br>Analytics for Social Networks<br>Real–time/Right–time and Event–based Analytics<br>Privacy and Security in Cloud Intelligence<br>Reliability and Fault tolerance in Cloud Intelligence<br>Big Data Application Design and Deployment<br>Data Mining Techniques: Clustering, Classification, Association Rules, Decision Trees, etc.<br>Data and Knowledge Representation<br>Knowledge Discovery Framework and Process, Including Pre– and Post–processing<br>Integration of Data Warehousing, OLAP and Data Mining<br>Integrating Constraints and Knowledge in the KDD Process<br>Exploring Data Analysis, Inference of Causes, Prediction<br>Evaluating, Consolidating, and Explaining Discovered Knowledge<br>Statistical Techniques for Generation a Robust, Consistent Data Model<br>Interactive Data Exploration/Visualization and Discovery<br>Languages and Interfaces for Data Mining<br>Cost Models for advanced applications and programming paradigms<br>Reproduction of Big Data Experiments<br>Big Data Data Mining Trends, Opportunities and Risks<br>Big Data Mining from Low–quality Information Sources<br>Track 2 – Industry and Application:<br>Big Data Analytics and Knowledge Discovery Tools<br>Big Data Deployment Industrial Experiences<br>Big Data Applications in Scientific, Government, Healthcare, Bioinformatics, Smart City, etc.<br>Big Data Analytics Applications in E–commerce and Web Technology for Finance, Healthcare, Marketing, Telecommunications, etc.<br>Big Data for Intrusion/Fraud Detection<br>Big Data and Business Process Intelligence (BPI)<br>Big Data in Enterprise Management Models and Practices<br>
Abbrevation
DaWaK
City
Lyon
Country
France
Deadline Paper
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