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» Negative Training Data Can be Harmful to Text Classification
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BMCBI
2010
143views more  BMCBI 2010»
14 years 9 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
ACL
2009
14 years 7 months ago
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge
Sentiment classification refers to the task of automatically identifying whether a given piece of text expresses positive or negative opinion towards a subject at hand. The prolif...
Tao Li, Yi Zhang 0005, Vikas Sindhwani
SIGMOD
2004
ACM
150views Database» more  SIGMOD 2004»
15 years 9 months ago
When one Sample is not Enough: Improving Text Database Selection Using Shrinkage
Database selection is an important step when searching over large numbers of distributed text databases. The database selection task relies on statistical summaries of the databas...
Panagiotis G. Ipeirotis, Luis Gravano
101
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TSP
2010
14 years 4 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
ELPUB
2007
ACM
15 years 1 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...