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KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 6 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
13 years 9 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 6 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
ICDM
2009
IEEE
223views Data Mining» more  ICDM 2009»
14 years 20 days ago
Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis
Abstract -- Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies ...
Qiang Fu, Jian-Guang Lou, Yi Wang, Jiang Li
KDD
2009
ACM
204views Data Mining» more  KDD 2009»
14 years 6 months ago
Improving classification accuracy using automatically extracted training data
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...