Name
Abstract | ||
|---|---|---|
Events are particularly important pieces of knowledge, as they represent activities of special significance within an organisation: the automated recognition of events is of utmost importance. We present RTEC, an Event Calculus dialect for run-time event recognition and its Prolog implementation. RTEC includes a number of novel techniques allowing for efficient run-time recognition, scalable to large data streams. It can be used in applications where data might arrive with a delay from, or might be revised by, the underlying event sources. We evaluate RTEC using a real-world application. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2335484.2335492 | DEBS |
Keywords | Field | DocType |
novel technique,important piece,run-time event recognition,efficient run-time recognition,real-world application,large data stream,run-time composite event recognition,event calculus dialect,automated recognition,prolog implementation,underlying event source,pattern matching,event processing,event calculus | Event calculus,Data mining,Data stream mining,Computer science,Complex event processing,Real-time computing,Prolog,Composite event,Pattern matching,Event recognition,Scalability | Conference |
Citations | PageRank | References |
24 | 1.24 | 23 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Artikis | 1 | 1142 | 82.51 |
| Marek Sergot | 2 | 549 | 56.98 |
| Georgios Paliouras | 3 | 1510 | 120.93 |