DaWaK 2020: Difference between revisions
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=== Scopes === | === Scopes === | ||
- Parallel Processing | * - Parallel Processing | ||
- Parallel DBMS Technology | * - Parallel DBMS Technology | ||
- Schema-free Data Repositories | * - Schema-free Data Repositories | ||
- Modelling diverse big data sources (e.g. text) | * - Modelling diverse big data sources (e.g. text) | ||
- Conceptual Model Foundations for Big Data | * - Conceptual Model Foundations for Big Data | ||
- Query Languages | * - Query Languages | ||
- Query processing and Optimization | * - Query processing and Optimization | ||
- Semantics for Big Data Intelligence | * - Semantics for Big Data Intelligence | ||
- Data Warehouses, Data Lakes | * - Data Warehouses, Data Lakes | ||
- Big Data Storage and Indexing | * - Big Data Storage and Indexing | ||
- Big Data Analytics: Algorithms, Techniques, and Systems | * - Big Data Analytics: Algorithms, Techniques, and Systems | ||
- Big Data Quality and Provenance Control | * - Big Data Quality and Provenance Control | ||
- Distributed System Architectures | * - Distributed System Architectures | ||
- Cloud Infrastructure for Big Data | * - Cloud Infrastructure for Big Data | ||
- Scalability and Parallelization using MapReduce, Spark and Related Systems | * - Scalability and Parallelization using MapReduce, Spark and Related Systems | ||
- Graph Analytics | * - Graph Analytics | ||
- Visualization | * - Visualization | ||
- Big Data Search and Discovery | * - Big Data Search and Discovery | ||
- Big Data Management for Mobile Applications | * - Big Data Management for Mobile Applications | ||
- Analytics for Unstructured, Semi-structured, and Structured Data | * - Analytics for Unstructured, Semi-structured, and Structured Data | ||
- Analytics for Temporal, Spatial, Spatio-temporal, and Mobile Data | * - Analytics for Temporal, Spatial, Spatio-temporal, and Mobile Data | ||
- Analytics for Data Streams and Sensor Data | * - Analytics for Data Streams and Sensor Data | ||
- Real-time/Right-time and Event-based Analytics | * - Real-time/Right-time and Event-based Analytics | ||
- Privacy and Security in Analytics | * - Privacy and Security in Analytics | ||
- Big Data Application Deployment | * - Big Data Application Deployment | ||
- Pre-processing and Data Cleaning | * - Pre-processing and Data Cleaning | ||
- Integration of Data Warehousing, OLAP Cubes and Data Mining | * - Integration of Data Warehousing, OLAP Cubes and Data Mining | ||
- Analytic Workflows | * - Analytic Workflows | ||
- Novel Applications of Text Mining to Big Data | * - Novel Applications of Text Mining to Big Data | ||
- Deep Learning Applications | * - Deep Learning Applications | ||
- Data Science Products | * - Data Science Products | ||
Revision as of 10:11, 7 May 2020
| DaWaK 2020 | |
|---|---|
22nd International Conference on Big Data Analytics and Knowledge Discovery
| |
| Event in series | DaWaK |
| Dates | 2020/09/14 (iCal) - 2020/09/17 |
| Homepage: | http://www.dexa.org/dawak2020 |
| Twitter account: | https://twitter.com/DEXASociety |
| Location | |
| Location: | Bratislava, Slovakia |
| Important dates | |
| Submissions: | 2020/04/14 |
| Table of Contents | |
| Tweets by https://twitter.com/DEXASociety | |
https://twitter.com/DEXASociety">Tweets by {{{Twitter account}}}
| |
Scopes
- - Parallel Processing
- - Parallel DBMS Technology
- - Schema-free Data Repositories
- - Modelling diverse big data sources (e.g. text)
- - Conceptual Model Foundations for Big Data
- - Query Languages
- - Query processing and 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
- - Cloud Infrastructure for Big Data
- - Scalability and Parallelization using MapReduce, Spark and Related Systems
- - Graph Analytics
- - 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
- - Real-time/Right-time and Event-based Analytics
- - Privacy and Security in Analytics
- - Big Data Application Deployment
- - Pre-processing and Data Cleaning
- - Integration of Data Warehousing, OLAP Cubes and Data Mining
- - Analytic Workflows
- - Novel Applications of Text Mining to Big Data
- - Deep Learning Applications
- - Data Science Products