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126
Voted
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
16 years 2 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»
15 years 5 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
93
Voted
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
16 years 2 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»
15 years 8 months 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»
16 years 2 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...