The Convergence of location-aware devices, wireless communication, such as the increasing accuracy of GPS technology and geographic information system functionalities enables the deployment of new services such as location-based services (LBS). Achieve high quality or such services, spatio-temporal data mining techniques are needed. Our work concentrates on the development of data mining techniques for knowledge discovery and delivery in LBS. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed.
The Convergence of location-aware devices, wireless communication, such as the increasing accuracy of GPS technology and geographic information system functionalities enables the deployment of new services such as location-based services (LBS). Achieve high quality or such services, spatio–temporal data mining techniques are needed. Our work concentrates on the development of data mining techniques for knowledge discovery and delivery in LBS. First, a number of real world spatio–temporal data sets are described, leading to a taxonomy of spatio–temporal data. Second, the paper describes a general methodology that transforms the spatio–temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio–temporal rules for LBS. Finally, unique issues in spatio–temporal rule mining are identified and discussed.