In stream reasoning, the task is to derive high level abstractions of large data streams with minimal latency, as required by contemporary applications. This work presents an Event Calculus-based approach to stream reasoning, highlighting its core features and recent extensions
Abstract. Since its introduction, the Event Calculus (EC) has been recognized for being an excellent...
We add branching time to the linear discrete event calculus, which yields a formalism for commonsens...
In recent years, there has been an increasing interest in extending stream processing engines with r...
Many "big data" applications must tame velocity (processing data in-motion) and variety (processing ...
We present a system for online, incremental composite event recognition. In streaming environments, ...
Abstract. The rise of smart applications has drawn interest to logi-cal reasoning over data streams....
Data streams occur in a variety of modern applications. Specialized Stream Database Management Syste...
In the last few years a new research area, called stream reasoning, emerged to bridge the gap betwee...
Streams of events appear increasingly today in various Web applications such as blogs, feeds, sensor...
In the last few years a new research area, called stream reasoning, emerged to bridge the gap betwee...
The recent rise of smart applications has drawn interest to logical reasoning over data streams. Dif...
The recent rise of smart applications has drawn interest to logical reasoning over data streams. Dif...
Since its introduction, the Event Calculus (EC) has been recognized for being an excellent framework...
The event calculus (EC) (Shanahan 1999) is a powerful and highly usable formalism for reasoning abou...
Abstract. The rise of smart applications has drawn interest to logical reason-ing over data streams....
Abstract. Since its introduction, the Event Calculus (EC) has been recognized for being an excellent...
We add branching time to the linear discrete event calculus, which yields a formalism for commonsens...
In recent years, there has been an increasing interest in extending stream processing engines with r...
Many "big data" applications must tame velocity (processing data in-motion) and variety (processing ...
We present a system for online, incremental composite event recognition. In streaming environments, ...
Abstract. The rise of smart applications has drawn interest to logi-cal reasoning over data streams....
Data streams occur in a variety of modern applications. Specialized Stream Database Management Syste...
In the last few years a new research area, called stream reasoning, emerged to bridge the gap betwee...
Streams of events appear increasingly today in various Web applications such as blogs, feeds, sensor...
In the last few years a new research area, called stream reasoning, emerged to bridge the gap betwee...
The recent rise of smart applications has drawn interest to logical reasoning over data streams. Dif...
The recent rise of smart applications has drawn interest to logical reasoning over data streams. Dif...
Since its introduction, the Event Calculus (EC) has been recognized for being an excellent framework...
The event calculus (EC) (Shanahan 1999) is a powerful and highly usable formalism for reasoning abou...
Abstract. The rise of smart applications has drawn interest to logical reason-ing over data streams....
Abstract. Since its introduction, the Event Calculus (EC) has been recognized for being an excellent...
We add branching time to the linear discrete event calculus, which yields a formalism for commonsens...
In recent years, there has been an increasing interest in extending stream processing engines with r...
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