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» Sentiment Mining Using Ensemble Classification Models
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CASCON
2004
129views Education» more  CASCON 2004»
13 years 9 months ago
Building predictors from vertically distributed data
Due in part to the large volume of data available today, but more importantly to privacy concerns, data are often distributed across institutional, geographical and organizational...
Sabine M. McConnell, David B. Skillicorn
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 8 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
ICDM
2010
IEEE
125views Data Mining» more  ICDM 2010»
13 years 5 months ago
Topic Modeling Ensembles
: Topic Modeling Ensembles Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen HP Laboratories HPL-2010-158 Topic model, Ensemble In this paper we propose a framework of topic model...
Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen
ELPUB
2007
ACM
13 years 11 months ago
Automatic Sentiment Analysis in On-line Text
The growing stream of content placed on the Web provides a huge collection of textual resources. People share their experiences on-line, ventilate their opinions (and frustrations...
Erik Boiy, Pieter Hens, Koen Deschacht, Marie-Fran...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...