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» Tight results for clustering and summarizing data streams
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DASFAA
2007
IEEE
178views Database» more  DASFAA 2007»
14 years 2 months ago
ClusterSheddy : Load Shedding Using Moving Clusters over Spatio-temporal Data Streams
Abstract. Moving object environments are characterized by large numbers of objects continuously sending location updates. At times, data arrival rates may spike up, causing the loa...
Rimma V. Nehme, Elke A. Rundensteiner
ICDE
2008
IEEE
157views Database» more  ICDE 2008»
14 years 9 months ago
Approximate Clustering on Distributed Data Streams
Abstract-- We investigate the problem of clustering on distributed data streams. In particular, we consider the k-median clustering on stream data arriving at distributed sites whi...
Qi Zhang, Jinze Liu, Wei Wang 0010
ICRA
2007
IEEE
151views Robotics» more  ICRA 2007»
14 years 2 months ago
Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks
— This paper presents a sensor analysis based fault detection approach (which we call SAFDetection) that is used to monitor tightly-coupled multi-robot team tasks. Our approach a...
Xingyan Li, Lynne E. Parker
KAIS
2006
164views more  KAIS 2006»
13 years 7 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
DAWAK
2004
Springer
14 years 1 months ago
SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes
Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorith...
Kok-Leong Ong, Wenyuan Li, Wee Keong Ng, Ee-Peng L...