TY - GEN
T1 - Distributed pattern discovery in multiple streams
AU - Sun, Jimeng
AU - Papadimitriou, Spiros
AU - Faloutsos, Christos
PY - 2006
Y1 - 2006
N2 - Given m groups of streams which consist of n1, . . . , n m coevolving streams in each group, we want to: (i) incrementally find local patterns within a single group, (ii) efficiently obtain global patterns across groups, and more importantly, (iii) efficiently do that in real time while limiting shared information across groups. In this paper, we present a distributed, hierarchical algorithm addressing these problems. Our experimental case study confirms that the proposed method can perform hierarchical correlation detection efficiently and effectively.1
AB - Given m groups of streams which consist of n1, . . . , n m coevolving streams in each group, we want to: (i) incrementally find local patterns within a single group, (ii) efficiently obtain global patterns across groups, and more importantly, (iii) efficiently do that in real time while limiting shared information across groups. In this paper, we present a distributed, hierarchical algorithm addressing these problems. Our experimental case study confirms that the proposed method can perform hierarchical correlation detection efficiently and effectively.1
UR - http://www.scopus.com/inward/record.url?scp=33745795772&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745795772&partnerID=8YFLogxK
U2 - 10.1007/11731139_82
DO - 10.1007/11731139_82
M3 - Conference contribution
AN - SCOPUS:33745795772
SN - 3540332065
SN - 9783540332060
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 713
EP - 718
BT - Advances in Knowledge Discovery and Data Mining - 10th Pacific-Asia Conference, PAKDD 2006, Proceedings
PB - Springer Verlag
T2 - 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2006
Y2 - 9 April 2006 through 12 April 2006
ER -