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|Title:||Continuous k-means monitoring over moving objects|
|Authors:||Zhang, Z. |
|Keywords:||k-means, continuous monitoring, query processing|
|Citation:||Zhang, Z., Yang, Y., Tung, A.K.H., Papadias, D. (2008). Continuous k-means monitoring over moving objects. IEEE Transactions on Knowledge and Data Engineering 20 (9) : 1205-1216. ScholarBank@NUS Repository. https://doi.org/10.1109/TKDE.2008.54|
|Abstract:||Given a data set P, a k-means query returns k points in space (called centers), such that the average squared distance between each point in P and its nearest center is minimized. Since this problem is NP-hard, several approximate algorithms have been proposed and used in practice. In this paper, we study continuous k-means computation at a server that monitors a set of moving objects. Reevaluating k-means every time there is an object update imposes a heavy burden on the server (for computing the centers from scratch) and the clients (for continuously sending location updates). We overcome these problems with a novel approach that significantly reduces the computation and communication costs, while guaranteeing that the quality of the solution, with respect to the reevaluation approach, is bounded by a user-defined tolerance. The proposed method assigns each moving object a threshold (i.e., range) such that the object sends a location update only when it crosses the range boundary. First, we develop an efficient technique for maintaining the k-means. Then, we present mathematical formulas and algorithms for deriving the individual thresholds. Finally, we justify our performance claims with extensive experiments. © 2008 IEEE.|
|Source Title:||IEEE Transactions on Knowledge and Data Engineering|
|Appears in Collections:||Staff Publications|
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