Snoop: an expressive event specification language for active databases
Data & Knowledge Engineering
TelegraphCQ: continuous dataflow processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Efficient pattern matching over event streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Plan-based complex event detection across distributed sources
Proceedings of the VLDB Endowment
Knowledge representation concepts for automated SLA management
Decision Support Systems
Stream Data Processing: A Quality of Service Perspective Modeling, Scheduling, Load Shedding, and Complex Event Processing
Towards semantic event processing
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
Semantic Rule-Based Complex Event Processing
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
Rule-based composite event queries: the language XChangeEQ and its semantics
RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
Processing flows of information: from data stream to complex event processing
Proceedings of the 5th ACM international conference on Distributed event-based system
Towards expressive publish/subscribe systems
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Anomaly management using complex event processing: extending data base technology paper
Proceedings of the 16th International Conference on Extending Database Technology
Hi-index | 0.00 |
Usage of background knowledge about events and their relations to other concepts in the application domain, can improve the quality of event processing. In this paper, we describe a system for knowledge-based event detection of complex stock market events based on available background knowledge about stock market companies. Our system profits from data fusion of live event stream and background knowledge about companies which is stored in a knowledge base. Users of our system can express their queries in a rule language which provides functionalities to specify semantic queries about companies in the SPARQL query language for querying the external knowledge base and combine it with event data stream. Background makes it possible to detect stock market events based on companies attributes and not only based on syntactic processing of stock price and volume.