Curator 91 (talk | contribs) (Created page with "{{Event |Acronym=ESWEEK 2020 |Title=Embedded Systems Week |Ordinal=16 |In Event Series=Event Series:Cdee022a-45e8-43ce-b77c-755268b309cf |Single Day Event=no |Start Date=2020/...") |
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{{Event | {{Event | ||
− | |Acronym= | + | |Acronym=DaWaK 2020 |
− | |Title= | + | |Title=22nd International Conference on Big Data Analytics and Knowledge Discovery |
− | | | + | |Type=Conference |
− | |In Event Series=Event Series: | + | |Homepage=http://www.dexa.org/dawak2020 |
+ | |Twitter account=https://twitter.com/DEXASociety | ||
+ | |City=Bratislava | ||
+ | |Country=Country:SK | ||
+ | |Submitting link=https://easychair.org/conferences/?conf=dawak2020 | ||
+ | |has general chair=Bernhard Moser | ||
+ | |has program chair=Min Song, Il-Yeol Song | ||
+ | |pageCreator=User:Curator 53 | ||
+ | |pageEditor=User:Curator 53 | ||
+ | |contributionType=1 | ||
+ | |In Event Series=Event Series:DaWaK | ||
|Single Day Event=no | |Single Day Event=no | ||
− | |Start Date=2020/09/ | + | |Start Date=2020/09/14 |
− | |End Date=2020/09/ | + | |End Date=2020/09/17 |
|Event Status=as scheduled | |Event Status=as scheduled | ||
− | |Event Mode= | + | |Event Mode=on site |
− | |||
}} | }} | ||
+ | {{Event Deadline | ||
+ | |Paper Deadline=2020/04/14 | ||
+ | |Notification Deadline=2020/05/20 | ||
+ | |Camera-Ready Deadline=2020/06/19 | ||
+ | |Submission Deadline=2020/04/14 | ||
+ | }} | ||
+ | {{Event Deadline}} | ||
+ | {{S Event}} | ||
+ | === 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 |
Revision as of 18:08, 22 September 2022
Deadlines
Deadlines
Venue
Warning: Venue is missing. The map might not show the exact location.
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