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DaWaK 2015 : 17th International Conference on Big Data Analytics and Knowledge Discovery - DaWaK 2015


Conference Series : Data Warehousing and Knowledge Discovery
When Sep 1, 2015 - Sep 4, 2015
Where Valencia, Spain
Abstract Registration Due Mar 17, 2015
Submission Deadline Mar 31, 2015
Notification Due May 19, 2015
Final Version Due Jun 9, 2015
Categories    databases   knowledge discovery   data warehousing   big data

Call For Papers

17th International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2015)
In conjunction with DEXA 2015 (

Valencia, Spain
September 1 - 5, 2015

Three Special Issues on the best papers from DAWAK '15 will be expanded and revised for possible inclusion in:

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.

Big Data Storage
Big Data Query Languages and Optimization
Big Data Analytics and User Interfaces
Big Data Indexing
Big Data Analytics: algorithms, techniques, and systems
Big Data Quality and Provenance Control
Social Networking Big Data Graph Management
Visualization Analytics for Big Data
Big Data Searching and Discovery
Big Data Management in Mobile Applications
Scalability and parallelization for cloud intelligence: map-reduce and beyond
Analytics for the cloud infrastructure
Analytics for unstructured, semi-structured, and structured data
Semantic web intelligence
Analytics for temporal, spatial, spatio-temporal, and mobile data
Analytics for data streams and sensor data
Analytics for 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
Data Mining Trends, Opportunities and Risks
Data Mining from low-quality information sources

Industry and Application Track:

Big Data Analytics and Knowledge Discovery Tools
Big Data Deployment Industryial Experiences
Big Data Applications in scientific, government, healthcare, bioinformatics, etc.
Big Data Analytics applications in E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc
Big Data and Business Process Intelligence (BPI)
Big Data in Enterprise Management Models and Practices
Big Data Applications in Smart City

Paper Submission Details

Authors are invited to submit research and application papers representing original, previously unpublished work. Papers should be submitted in PDF or Word format. Submission Online at: DaWaK 2015 Submission site starting in January 2015.

Submissions must conform to Springer's LNCS format and should not exceed 12 pages. All accepted papers will be published in LNCS by Springer-Verlag.

Authors of selected best papers from DaWaK 2015 will be invited to submit the extended paper for special issues of Distributed and Parallel Databases and LNCS Transactions on Large-Scale Data and Knowledge-Centered Systems.

For further inquiries, contact the DaWaK 2015 PC chairs


Submission of abstracts: March 17, 2015
Submission of full papers: March 31, 2015
Notification of acceptance: May 19, 2015
Camera-ready copies due: June 09, 2015

Program Chairs

Sanjay K Madria, Missouri University of Science and Technology, USA (
Takahiro Hara, Osaka University, Japan ( )

Program Committee


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