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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 6 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...
MOBISYS
2009
ACM
16 years 6 days ago
SolarStore: enhancing data reliability in solar-powered storage-centric sensor networks
In this paper, we present a reliable storage service, called SolarStore, that adaptively trades-off storage reliability versus energy consumption in solar-powered sensor networks....
Yong Yang, Lili Wang, Dong Kun Noh, Hieu Khac Le, ...
122
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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 2 days ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 2 days ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
SIGMOD
2009
ACM
190views Database» more  SIGMOD 2009»
15 years 12 months ago
Optimizing complex extraction programs over evolving text data
Most information extraction (IE) approaches have considered only static text corpora, over which we apply IE only once. Many real-world text corpora however are dynamic. They evol...
Fei Chen 0002, Byron J. Gao, AnHai Doan, Jun Yang ...