Massive streaming data analytics: A case study with clustering coefficients

Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2010

Volumn , Issue , 2010, Pages

  Ediger, David ^a   Jiang, Karl ^a   Riedy, Jason ^a   Bader, David A ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS AND DATA STRUCTURES; APPROXIMATION METHODS; BLOOM FILTERS; CLUSTERING COEFFICIENT; FORCE METHOD; HIGH DATA RATE; INCREMENTAL UPDATES; INPUT DATAS; LOCAL CLUSTERING; MASSIVE GRAPH; NEW APPROACHES; PERFORMANCE COSTS; RECOMPUTATION; SCALE FREE GRAPH; SOCIAL NETWORKS; SORTING ALGORITHM; STREAMING DATA; TEMPORAL DATA;

APPROXIMATION ALGORITHMS; APPROXIMATION THEORY; BLOOMS (METAL); CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; DATA STRUCTURES; DISTRIBUTED PARAMETER NETWORKS; HEALTH CARE;

SECURITY OF DATA;

EID: 77954040562     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPSW.2010.5470687     Document Type: Conference Paper

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