In this paper we study in-network query processing in disconnected mobile environments, where both ad-hoc communication and infrastructure communication are available. Depending o...
In this paper, we discuss an application of spatial data mining to predict pedestrian flow in extensive road networks using a large biased sample. Existing out-of-the-box techniqu...
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
A number of algorithms of clustering spatial data for reducing the number of disk seeks required to process spatial queries have been developed. One of the algorithms is the scheme...
In this paper, we present a general framework to discover spatial associations and spatio-temporal episodes for scientific datasets. In contrast to previous work in this area, fea...