Name
Abstract | ||
|---|---|---|
Urban environments are increasingly invaded by devices that acquire sensor information and pave the way for innovative forms of context awareness. Collecting knowledge from loosely-structured data streams and reasoning about changes are two key elements of the process. This paper illustrates a possible way to combine these two elements in a coordinated way. We make use of a recently-developed framework for classifying data streams with service-oriented, reconfigurable components. Furthermore, we embed the KnowLang Reasoner, allowing logical and statistical reasoning on the acquired knowledge aiming to achieve self-adaptation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-15392-6_3 | Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering |
Field | DocType | Volume |
Data science,Data mining,Data stream mining,Logical conjunction,Semantic reasoner,Data stream,Situation awareness,Computer science,Context awareness,Bayesian network,Smart city | Conference | 144 |
ISSN | Citations | PageRank |
1867-8211 | 1 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicola Bicocchi | 1 | 233 | 22.11 |
| Emil Vassev | 2 | 263 | 41.81 |
| Franco Zambonelli | 3 | 4662 | 330.78 |
| Mike Hinchey | 4 | 494 | 51.89 |