מרק לסט

אקדמי בכיר

Discovering regular groups of mobile objects using incremental clustering

Sigal Elnekave, Mark Last, Oded Maimon, Yehuda Ben-Shimol, Hans Einsiedler, Menahem Friedman, Matthias Siebert

As technology advances, detailed data on the position of moving objects, such as humans and vehicles is available. In order to discover groups of mobile objects that usually move in similar ways we propose an incremental clustering algorithm that clusters mobile objects according to similarity of their movement patterns. The proposed clustering algorithm uses a new, "data-amount- based" similarity measure between mobile trajectories. The clustering algorithm is evaluated on two spatio-temporal datasets using clustering validity measures.

שפת פרסום אנגלית
דפים 197-205
סטטוס פרסום פורסם - 15.09.2008
מספר מאמר 4510375

Keywords

Clustering
Mobile objects
Spatio-temporal data mining

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering
Communication
גישה למסמך
10.1109/WPNC.2008.4510375
קבצים וקישורים אחרים
Link to publication in Scopus