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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 9 days ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
IPPS
2010
IEEE
14 years 9 months ago
Improving MapReduce performance through data placement in heterogeneous Hadoop clusters
MapReduce has become an important distributed processing model for large-scale data-intensive applications like data mining and web indexing. Hadoop
Jiong Xie, Shu Yin, Xiaojun Ruan, Zhiyang Ding, Yu...
CIKM
2009
Springer
15 years 6 months ago
Mining frequent itemsets in time-varying data streams
Mining frequent itemsets in data streams is beneficial to many real-world applications but is also a challenging task since data streams are unbounded and have high arrival rates...
Yingying Tao, M. Tamer Özsu
HPDC
2008
IEEE
15 years 6 months ago
Issues in applying data mining to grid job failure detection and diagnosis
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
Lakshmikant Shrinivas, Jeffrey F. Naughton
SIGMOD
2006
ACM
148views Database» more  SIGMOD 2006»
15 years 12 months ago
Research issues in data stream association rule mining
There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring and web click streams analysis. Different from data in t...
Nan Jiang, Le Gruenwald