Pervasive parallelism in data mining: Dataflow solution to co-clustering large and sparse netflix data

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2009, Pages 1115-1123

  Daruru, Srivatsava ^a   Marín, Nena ^b   Walker, Matt ^b   Ghosh, Joydeep ^c  

^a University of Texas at Austin   (United States)

^b Pervasive Software   (United States)

^c The University of Texas at Austin   (United States)

Author keywords

Co slustering; Dataflow; Predictive modeling; Scalability

Indexed keywords

CO-CLUSTERING; CO-CLUSTERS; CO-SLUSTERING; COLLABORATIVE FILTERING; DATA MINING APPLICATIONS; DATA SETS; DATAFLOW; DOMAIN KNOWLEDGE; LARGE-SCALE PRODUCTION; MEMORY MANAGEMENT; MULTI CORE; PARALLEL PROGRAM; PREDICTIVE MODELING; REAL-TIME PREDICTION; RUNTIMES; TRAINING DATASET;

FILTRATION; PARALLEL ARCHITECTURES; SCALABILITY;

DATA FLOW ANALYSIS;

EID: 70350647580     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1557019.1557140     Document Type: Conference Paper

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