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KDD
2009
ACM
232views Data Mining» more  KDD 2009»
16 years 7 months ago
Classification of software behaviors for failure detection: a discriminative pattern mining approach
Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 7 months 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...
PODS
2009
ACM
112views Database» more  PODS 2009»
16 years 7 months ago
Optimal sampling from sliding windows
APPEARED IN ACM PODS-2009. A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are disc...
Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniol...
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 6 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 6 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...