Name
Abstract | ||
|---|---|---|
This paper describes key modelling concepts for events, event patterns and related concepts needed to develop a distributed software framework for real-time business analytics. These concepts are specified by means of a minimal meta-model, whose implementation can enable better interoperability between different event processing systems. This in turn can support better, distributed, collaborative analytics applications in many domains. We show an implementation of our solution approach using a case study of several business analytics problems in finance. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/EDOC.2015.26 | EDOC |
Keywords | Field | DocType |
Complex Event Processing, real-time analytics, finance applications | Data science,Data mining,Business analytics,Software analytics,Web analytics,Interoperability,Computer science,Complex event processing,Semantic analytics,Analytics,Business intelligence,Finance | Conference |
ISSN | Citations | PageRank |
2325-6354 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zoran Milosevic | 1 | 548 | 54.38 |
| Andrew Berry | 2 | 0 | 0.34 |
| Weisi Chen | 3 | 1 | 2.10 |
| Fethi Rabhi | 4 | 427 | 50.68 |