Conference Information
DaWaK 2020: International Conference on Data Warehousing and Knowledge Discovery
http://www.dexa.org/dawak2020Submission Date: |
2020-04-14 Extended |
Notification Date: |
2020-05-20 |
Conference Date: |
2020-09-14 |
Location: |
Bratislava, Slovakia |
Years: |
22 |
CORE: b QUALIS: b1 Viewed: 10563 Tracked: 5 Attend: 0
Call For Papers
The annual DaWaK conference is a high-quality forum for researchers, practitioners and developers in the field of Big Data Analytics, in a broad sense. The objective is to explore, disseminate and exchange knowledge in this field through scientific and industry talks. The conference covers all aspects of DaWaK research and practice, including data lakes (schema-free repositories), database design (data warehouse design, ER modeling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, bringing together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide. Theoretical Models for Extended Data Warehouses and Big Data Parallel Processing Parallel DBMS technology Schema-free data repositories Modeling diverse big data sources (e.g. text) Conceptual Model Foundations for Big Data Query Languages Query processing and Optimization Cost Models for advanced optimization Semantics for Big Data Intelligence Data warehouses, data lakes Big Data Storage and Indexing Big Data Analytics: algorithms, techniques, and systems Big Data Quality and Provenance Control Distributed system architectures Exploiting hardware to accelerate processing: multicore CPUs, cache memory, GPUs Cloud Infrastructure to manage big data Scalability and Parallelization using MapReduce, Spark and related systems Graph analytics, including social networks and the Internet Visualization Big Data Search and Discovery Big Data Management for Mobile Applications Analytics for Unstructured, Semi-structured, and Structured Data Analytics for Temporal, Spatial, Spatio-temporal, and Mobile Data Analytics for Data Streams and Sensor Data Analytics for Big Multimedia Data Real-time/Right-time and Event-based Analytics Privacy and Security in Analytics Big Data Application Deployment Pre-processing and data cleaning to build analytic data sets Integration of Data Warehousing, OLAP Cubes and Data Mining Analytic workflows
Last updated by Dou Sun in 2020-04-10
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Related Journals
CCF | Full Name | Impact Factor | Publisher | ISSN |
---|---|---|---|---|
b | ACM Transactions on Knowledge Discovery from Data | ACM | 1556-4681 | |
b | Data & Knowledge Engineering | 1.583 | Elsevier | 0169-023X |
c | International Journal of Software Engineering and Knowledge Engineering | World Scientific | 0218-1940 | |
International Journal of Data Mining & Knowledge Management Process | AIRCC | 2231-007X | ||
Materials Discovery | Elsevier | 2352-9245 | ||
Journal of Materials Processing Technology | 4.178 | Elsevier | 0924-0136 | |
a | IEEE Transactions on Knowledge and Data Engineering | 3.857 | IEEE | 1041-4347 |
Language Learning & Technology | 2.571 | University of Hawaii Press | 1094-3501 | |
c | Journal of Experimental and Theoretical Artificial Intelligence | 1.384 | Taylor & Francis | 0952-813X |
c | Machine Vision and Applications | 2.005 | Springer | 0932-8092 |
Full Name | Impact Factor | Publisher |
---|---|---|
ACM Transactions on Knowledge Discovery from Data | ACM | |
Data & Knowledge Engineering | 1.583 | Elsevier |
International Journal of Software Engineering and Knowledge Engineering | World Scientific | |
International Journal of Data Mining & Knowledge Management Process | AIRCC | |
Materials Discovery | Elsevier | |
Journal of Materials Processing Technology | 4.178 | Elsevier |
IEEE Transactions on Knowledge and Data Engineering | 3.857 | IEEE |
Language Learning & Technology | 2.571 | University of Hawaii Press |
Journal of Experimental and Theoretical Artificial Intelligence | 1.384 | Taylor & Francis |
Machine Vision and Applications | 2.005 | Springer |
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