Paper Info
Title
Multidimensional Analysis of Atypical Events in Cyber-Physical Data
Abstract
A Cyber-Physical System (CPS) integrates physical devices (e.g., sensors, cameras) with cyber (or informational) components to form a situation-integrated analytical system that may respond intelligently to dynamic changes of the real-world situations. CPS claims many promising applications, such as traffic observation, battlefield surveillance and sensor-network based monitoring. One important research topic in CPS is about the atypical event analysis, i.e., retrieving the events from large amount of data and analyzing them with spatial, temporal and other multi-dimensional information. Many traditional approaches are not feasible for such analysis since they use numeric measures and cannot describe the complex atypical events. In this study, we propose a new model of atypical cluster to effectively represent those events and efficiently retrieve them from massive data. The micro-cluster is designed to summarize individual events, and the macro-cluster is used to integrate the information from multiple event. To facilitate scalable, flexible and online analysis, the concept of significant cluster is defined and a guided clustering algorithm is proposed to retrieve significant clusters in an efficient manner. We conduct experiments on real datasets with the size of more than 50 GB, the results show that the proposed method can provide more accurate information with only 15% to 20% time cost of the baselines.
Year
DOI
Venue
2012
10.1109/ICDE.2012.32
ICDE
Keywords
Field
DocType
sensor-network based monitoring,multidimensional analysis,atypical cluster,complex atypical event,pattern clustering,atypical event analysis,battlefield surveillance,accurate information,information integration,clustering algorithm,cyber-physical system,multiple event,atypical events,individual event,data analysis,cps,cyber-physical data,numeric measures,traffic observation,microcluster,macrocluster,traffic information systems,massive data,multi-dimensional information,situation-integrated analytical system,online analysis,significant cluster,cyber physical system,clustering algorithms,indexation,indexes,cyber physical systems,sensor network
Information integration,Data mining,Online analysis,Battlefield,Computer science,Multidimensional analysis,Cyber-physical system,Cluster analysis,Event analysis,Database,Scalability
Conference
ISSN
ISBN
Citations 
1063-6382
978-1-4673-0042-1
2
PageRank 
References 
Authors
0.40
11
8
Name
Order
Citations
PageRank
Lu An Tang142727.74
Xiao Yu267928.10
Sangkyum Kim317810.54
Jiawei Han4430853824.48
Wen-Chih Peng51645106.49
Yizhou Sun63446143.93
Hector Gonzalez763433.11
Sebastian Seith820.40