Name
Abstract | ||
|---|---|---|
The technologies of mobile communications and ubiquitous computing pervade society. Wireless networks sense the movement of people and vehicles, generating large volumes of mobility data, such as mobile phone call records and GPS tracks. This data can produce useful knowledge, supporting sustainable mobility and intelligent transportation systems, provided that a suitable knowledge discovery process is enacted for mining this mobility data. In this paper, the authors examine a formal framework, and the associated implementation, for a data mining query language for mobility data, created as a result of a European-wide research project called GeoPKDD Geographic Privacy-Aware Knowledge Discovery and Delivery. The authors discuss how the system provides comprehensive support for the Mobility Knowledge Discovery process and illustrate its analytical power in unveiling the complexity of urban mobility in a large metropolitan area, based on a massive real life GPS dataset. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.4018/jdwm.2011010102 | IJDWM |
Keywords | Field | DocType |
mobility knowledge discovery process,large metropolitan area,mobile communication,query language,large volume,geopkdd geographic privacy-aware knowledge,data mining query language,mobility data,massive real life gps,mobility data mining,urban mobility,sustainable mobility,data mining,gps,mobility | Data mining,Data stream mining,Query language,World Wide Web,RDF query language,Computer science,Mobility model,Knowledge extraction,Ubiquitous computing,Mobile phone,Intelligent transportation system | Journal |
Volume | Issue | ISSN |
7 | 1 | 1548-3924 |
Citations | PageRank | References |
18 | 1.63 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Trasarti | 1 | 710 | 45.82 |
| Fosca Giannotti | 2 | 2948 | 253.39 |
| Mirco Nanni | 3 | 1412 | 84.47 |
| Dino Pedreschi | 4 | 3083 | 244.47 |
| Chiara Renso | 5 | 925 | 76.04 |