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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
15 years 10 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...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
15 years 10 months ago
Extracting shared subspace for multi-label classification
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...
Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
15 years 10 months ago
Structured entity identification and document categorization: two tasks with one joint model
Traditionally, research in identifying structured entities in documents has proceeded independently of document categorization research. In this paper, we observe that these two t...
Indrajit Bhattacharya, Shantanu Godbole, Sachindra...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
15 years 10 months 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
2008
ACM
172views Data Mining» more  KDD 2008»
15 years 10 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon