Sciweavers

49 search results - page 2 / 10
» On Semi-Supervised Classification
Sort
View
FLAIRS
2004
13 years 6 months ago
Semi-Supervised Sequence Classification with HMMs
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Shi Zhong
COLING
2010
12 years 11 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang
ICDM
2005
IEEE
217views Data Mining» more  ICDM 2005»
13 years 10 months ago
Improving Automatic Query Classification via Semi-Supervised Learning
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
PAMI
2010
225views more  PAMI 2010»
12 years 11 months ago
Semi-Supervised Classification via Local Spline Regression
Abstract--This paper presents local spline regression for semisupervised classification. The core idea in our approach is to introduce splines developed in Sobolev space to map the...
Shiming Xiang, Feiping Nie, Changshui Zhang
AMT
2006
Springer
147views Multimedia» more  AMT 2006»
13 years 8 months ago
Semi-Supervised Text Classification Using Positive and Unlabeled Data
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
Shuang Yu, Xueyuan Zhou, Chunping Li