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» Sampling the Web as Training Data for Text Classification
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WWW
2007
ACM
16 years 3 months ago
Web page classification with heterogeneous data fusion
Web pages are more than text and they contain much contextual and structural information, e.g., the title, the meta data, the anchor text, etc., each of which can be seen as a dat...
Zenglin Xu, Irwin King, Michael R. Lyu
SIGIR
2000
ACM
15 years 7 months ago
Hierarchical classification of Web content
This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train diffe...
Susan T. Dumais, Hao Chen
COLING
2008
15 years 4 months ago
Automatic Seed Word Selection for Unsupervised Sentiment Classification of Chinese Text
We describe and evaluate a new method of automatic seed word selection for unsupervised sentiment classification of product reviews in Chinese. The whole method is unsupervised an...
Taras Zagibalov, John Carroll
AAAI
1998
15 years 4 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
ICDM
2010
IEEE
132views Data Mining» more  ICDM 2010»
15 years 1 months ago
Monotone Relabeling in Ordinal Classification
In many applications of data mining we know beforehand that the response variable should be increasing (or decreasing) in the attributes. Such relations between response and attrib...
Ad Feelders