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WWW
2005
ACM
16 years 3 months ago
Improving recommendation lists through topic diversification
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
142
Voted
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
16 years 3 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 3 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
161views Data Mining» more  KDD 2008»
16 years 3 months ago
Locality sensitive hash functions based on concomitant rank order statistics
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kave Eshghi, Shyamsundar Rajaram
122
Voted
KDD
2008
ACM
213views Data Mining» more  KDD 2008»
16 years 3 months ago
Heterogeneous data fusion for alzheimer's disease study
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...