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KDD
2009
ACM
207views Data Mining» more  KDD 2009»
15 years 10 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
KDD
2009
ACM
193views Data Mining» more  KDD 2009»
15 years 10 months ago
Probabilistic frequent itemset mining in uncertain databases
Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
Andreas Züfle, Florian Verhein, Hans-Peter Kr...
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
15 years 10 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
KDD
2009
ACM
202views Data Mining» more  KDD 2009»
15 years 10 months ago
Correlated itemset mining in ROC space: a constraint programming approach
Correlated or discriminative pattern mining is concerned with finding the highest scoring patterns w.r.t. a correlation measure (such as information gain). By reinterpreting corre...
Siegfried Nijssen, Tias Guns, Luc De Raedt
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
15 years 10 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee