DaWaK 2017 : Data Warehousing and Knowledge Discovery (DaWaK)

  in Conferences   Posted on July 31, 2017

Conference Information

Submission Deadline Monday 20 Mar 2017
Conference & Submission Link http://www.dexa.org/dawak2017
Conference Dates Aug 28, 2017 - Aug 31, 2017
Conference Address Lyon, France
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Google Scholar H5-index: 13
CORE 2017 Rating: B
Guide2Research Overall Ranking: 355
Category Rankings
Databases & Information Systems 79
Machine Learning & Arti. Intelligence 89

Conference Call for Papers

The best papers from DAWAK \’17 will be expanded and revised for possible inclusion in:

Journal of Concurrency and Computation: Practice and Experience, Wiley
Distributed and Parallel Databases, Springer
Transactions on Large-scale Data- and Knowledge Centered Systems – TLDKS

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.
Track 1 – Research:

Big Data Query Languages and Optimization
Big Data Analytics and User Interfaces
Big Data Indexing and Storing
Big Data Analytics: algorithms, techniques, and systems
Big Data Quality and Provenance Control
Social Networking Data Graph Management
Graph mining, analysis, and querying.
Visualization Analytics for Big Data
Big Data Searching and Discovery
Big Data Management for Mobile Applications
Scalability and Parallelization using Mapreduce and beyond
Analytics for the Cloud Infrastructure
Analytics for Unstructured, Semi-structured, and Structured Data
Semantic for Big Data Intelligence
Analytics for Temporal, Spatial, Spatio-temporal, and Mobile Data
Analytics for Data Streams and Sensor Data
Analytics for Big Multimedia Data
Analytics for Social Networks
Real-time/Right-time and Event-based Analytics
Privacy and Security in Cloud Intelligence
Reliability and Fault tolerance in Cloud Intelligence
Big Data Application Design and Deployment
Data Mining Techniques: Clustering, Classification, Association Rules, Decision Trees, etc.
Data and Knowledge Representation
Knowledge Discovery Framework and Process, Including Pre- and Post-processing
Integration of Data Warehousing, OLAP and Data Mining
Integrating Constraints and Knowledge in the KDD Process
Exploring Data Analysis, Inference of Causes, Prediction
Evaluating, Consolidating, and Explaining Discovered Knowledge
Statistical Techniques for Generation a Robust, Consistent Data Model
Interactive Data Exploration/Visualization and Discovery
Languages and Interfaces for Data Mining
Cost Models for advanced applications and programming paradigms
Reproduction of Big Data Experiments
Big Data Data Mining Trends, Opportunities and Risks
Big Data Mining from Low-quality Information Sources

Track 2 – Industry and Application:

Big Data Analytics and Knowledge Discovery Tools
Big Data Deployment Industrial Experiences
Big Data Applications in Scientific, Government, Healthcare, Bioinformatics, Smart City, etc.
Big Data Analytics Applications in E-commerce and Web Technology for Finance, Healthcare, Marketing, Telecommunications, etc.
Big Data for Intrusion/Fraud Detection
Big Data and Business Process Intelligence (BPI)
Big Data in Enterprise Management Models and Practices

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