ACM Symposium on Applied Computing
Data Streams Track
Data Streams Track
in conjunction with
ACM Symposium on Applied Computing:
The 29th Annual ACM Symposium on Applied Computing
in Gyeongju, Korea, March 24 - 28, 2014.
2 Topics
A data stream is an ordered sequence of instances that can be read only once or a small number of times. Topics include but are not restricted to:
- Data Stream Models
- Languages for Stream Query
- Continuous Queries
- Clustering from Data Streams
- Decision Trees from Data Streams
- Association Rules from Data Streams
- Decision Rules from Data Streams
- Bayesian networks from Data Streams
- Feature Selection from Data Streams
- Visualization Techniques for Data Streams
- Incremental on-line Learning Algorithms
- Single-Pass Algorithms
- Temporal, spatial, and spatio-temporal data mining
- Scalable Algorithms
- Real-Time and Real-World Applications using Stream data
- Distributed Stream Mining
- Social Network Stream Mining