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» Unsupervised Feature Selection for Text Data
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NIPS
2001
13 years 9 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 8 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
ICDM
2008
IEEE
107views Data Mining» more  ICDM 2008»
14 years 2 months ago
Graph-Based Iterative Hybrid Feature Selection
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, J...
HICSS
2007
IEEE
134views Biometrics» more  HICSS 2007»
14 years 2 months ago
Exploring the Clinical Notes of Pathology Ordering by Australian General Practitioners: a text mining perspective
A massive rise in the number and expenditure of pathology ordering by general practitioners (GPs) concerns the government and attracts various studies with the aim to understand a...
Zoe Yan Zhuang, Rasika Amarasiri, Leonid Churilov,...
SGAI
2007
Springer
14 years 1 months ago
Selecting Bi-Tags for Sentiment Analysis of Text
Sentiment Analysis aims to determine the overall sentiment orientation of a given input text. One motivation for research in this area is the need for consumer related industries t...
Rahman Mukras, Nirmalie Wiratunga, Robert Lothian