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AAAI
2007
13 years 10 months ago
Learning Large Scale Common Sense Models of Everyday Life
Recent work has shown promise in using large, publicly available, hand-contributed commonsense databases as joint models that can be used to infer human state from day-to-day sens...
William Pentney, Matthai Philipose, Jeff A. Bilmes...
MSV
2004
13 years 9 months ago
MABAC - Matrix Based Clustering Algorithm
Clustering is a prominent method in the data mining field. It is a discovery process that groups data such that intra cluster similarity is maximized and the inter cluster similar...
Yonghui Chen, Alan P. Sprague, Kevin D. Reilly
KDD
2008
ACM
153views Data Mining» more  KDD 2008»
14 years 8 months ago
Information extraction from Wikipedia: moving down the long tail
Not only is Wikipedia a comprehensive source of quality information, it has several kinds of internal structure (e.g., relational summaries known as infoboxes), which enable self-...
Fei Wu, Raphael Hoffmann, Daniel S. Weld
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 8 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
ADMA
2006
Springer
143views Data Mining» more  ADMA 2006»
13 years 11 months ago
Robust Collective Classification with Contextual Dependency Network Models
Abstract. In order to exploit the dependencies in relational data to improve predictions, relational classification models often need to make simultaneous statistical judgments abo...
YongHong Tian, Tiejun Huang, Wen Gao