TY - GEN
T1 - Adaptive multimedia mining on distributed stream processing systems
AU - Turaga, Deepak S.
AU - Park, Hyunggon
AU - Yan, Rong
AU - Verscheure, Olivier
PY - 2010
Y1 - 2010
N2 - We present an application for distributed semantic concept detection in multimedia streams. The streams are mined using Support Vector Machine based concept detectors (classifiers) deployed on a distributed stream processing system. We organize the classifiers into a hierarchical topology based on semantic relationships between the concepts of interest, and use the system resource manager to place the topology across a set of processing nodes. We then develop distributed game theoretic optimization strategies for dynamic adaptation of individual classifier operating characteristics in order to maximize end-to-end application utility under varying resource availability. As part of this paper, we will demonstrate the principles behind large-scale multimedia stream mining, and showcase the design, development, deployment, and distributed adaptation of such applications on a large scale cluster. A video demonstration of the system can be found at: http://childman.bol.ucla.edu/ICDM/ demovideoicdm2009.swf
AB - We present an application for distributed semantic concept detection in multimedia streams. The streams are mined using Support Vector Machine based concept detectors (classifiers) deployed on a distributed stream processing system. We organize the classifiers into a hierarchical topology based on semantic relationships between the concepts of interest, and use the system resource manager to place the topology across a set of processing nodes. We then develop distributed game theoretic optimization strategies for dynamic adaptation of individual classifier operating characteristics in order to maximize end-to-end application utility under varying resource availability. As part of this paper, we will demonstrate the principles behind large-scale multimedia stream mining, and showcase the design, development, deployment, and distributed adaptation of such applications on a large scale cluster. A video demonstration of the system can be found at: http://childman.bol.ucla.edu/ICDM/ demovideoicdm2009.swf
KW - Large-scale mining
KW - Multimedia mining
KW - Resource adaptive mining
KW - Semantic concept detection
KW - Stream processing
UR - http://www.scopus.com/inward/record.url?scp=79951742652&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2010.159
DO - 10.1109/ICDMW.2010.159
M3 - Conference contribution
AN - SCOPUS:79951742652
SN - 9780769542577
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 1419
EP - 1422
BT - Proceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
T2 - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
Y2 - 14 December 2010 through 17 December 2010
ER -