Paper Info
Title
Knowledge-based processing of complex stock market events
Abstract
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.
Year
DOI
Venue
2012
10.1145/2247596.2247674
EDBT
Keywords
Field
DocType
knowledge-based event detection,knowledge base,available background knowledge,knowledge-based processing,complex stock market event,external knowledge base,event processing,event data stream,live event stream,companies attribute,data fusion,profitability,complex event processing,query language,modeling techniques
Data science,Data mining,Computer science,Complex event processing,SPARQL,Sensor fusion,Application domain,Knowledge base,Syntax,Stock market,Database,Profit (economics)
Conference
Citations 
PageRank 
References 
9
0.60
15
Authors
3
Name
Order
Citations
PageRank
Kia Teymourian114215.27
Malte Rohde2321.96
Adrian Paschke3983128.61