We face today a paradigm shift toward the real time information processing, and Event Processing (EP) has therefore spawned significant attention in science and technology. Due to omnipresence of events, EP is becoming a central aspect of new distributed systems such as cloud computing and smart grid systems, mobile and sensor-based systems, as well as of a number of application areas including financial services, business intelligence, social and collaborative networking, click stream analysis…
We face today a paradigm shift toward the real time information processing, and Event Processing (EP) has therefore spawned significant attention in science and technology. Due to omnipresence of events, EP is becoming a central aspect of new distributed systems such as cloud computing and smart grid systems, mobile and sensor-based systems, as well as of a number of application areas including financial services, business intelligence, social and collaborative networking, click stream analysis and others. However in many applications to process only events is insufficient. Detection of complex situations very often involves evaluation of background knowledge too. This knowledge captures the domain of interest (context). This book presents the ETALIS Language for Events (ELE), which is a declarative rule-based language for processing events in the context of background (domain) knowledge. The book explores how stream reasoning capabilities together with EP capabilities of ELE have the potential to provide powerful real time intelligence. Finally, to demonstrate usefulness of ETALIS approach, the book presents a few scenarios with an existing open source implementation.
We face today a paradigm shift toward the real time information processing, and Event Processing (EP) has therefore spawned significant attention in science and technology. Due to omnipresence of events, EP is becoming a central aspect of new distributed systems such as cloud computing and smart grid systems, mobile and sensor-based systems, as well as of a number of application areas including financial services, business intelligence, social and collaborative networking, click stream analysis and others. However in many applications to process only events is insufficient. Detection of complex situations very often involves evaluation of background knowledge too. This knowledge captures the domain of interest (context). This book presents the ETALIS Language for Events (ELE), which is a declarative rule-based language for processing events in the context of background (domain) knowledge. The book explores how stream reasoning capabilities together with EP capabilities of ELE have the potential to provide powerful real time intelligence. Finally, to demonstrate usefulness of ETALIS approach, the book presents a few scenarios with an existing open source implementation.
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