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KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 7 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
186
Voted
ICDM
2008
IEEE
136views Data Mining» more  ICDM 2008»
16 years 1 months ago
Document-Word Co-regularization for Semi-supervised Sentiment Analysis
The goal of sentiment prediction is to automatically identify whether a given piece of text expresses positive or negative opinion towards a topic of interest. One can pose sentim...
Vikas Sindhwani, Prem Melville
ICDM
2008
IEEE
142views Data Mining» more  ICDM 2008»
16 years 1 months ago
Clustering Events on Streams Using Complex Context Information
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
YongChul Kwon, Wing Yee Lee, Magdalena Balazinska,...
KDD
2007
ACM
210views Data Mining» more  KDD 2007»
16 years 26 days ago
Machine learning for stock selection
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Robert J. Yan, Charles X. Ling
CIKM
2008
Springer
15 years 8 months ago
Characterizing and predicting community members from evolutionary and heterogeneous networks
Mining different types of communities from web data have attracted a lot of research efforts in recent years. However, none of the existing community mining techniques has taken i...
Qiankun Zhao, Sourav S. Bhowmick, Xin Zheng, Kai Y...