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ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 3 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
KDD
2007
ACM
124views Data Mining» more  KDD 2007»
14 years 2 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
KDD
2005
ACM
178views Data Mining» more  KDD 2005»
14 years 2 months ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 2 months ago
Combining partitions by probabilistic label aggregation
Data clustering represents an important tool in exploratory data analysis. The lack of objective criteria render model selection as well as the identification of robust solutions...
Tilman Lange, Joachim M. Buhmann
WKDD
2010
CPS
204views Data Mining» more  WKDD 2010»
14 years 2 months ago
A Scalable, Accurate Hybrid Recommender System
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...
Mustansar Ali Ghazanfar, Adam Prügel-Bennett