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» Text classification improved through multigram models
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ML
2000
ACM
124views Machine Learning» more  ML 2000»
13 years 5 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
SIGIR
2004
ACM
13 years 11 months ago
Web-page classification through summarization
Web-page classification is much more difficult than pure-text classification due to a large variety of noisy information embedded in Web pages. In this paper, we propose a new Web...
Dou Shen, Zheng Chen, Qiang Yang, Hua-Jun Zeng, Be...
QSIC
2007
IEEE
13 years 11 months ago
Automatic Quality Assessment of SRS Text by Means of a Decision-Tree-Based Text Classifier
The success of a software project is largely dependent upon the quality of the Software Requirements Specification (SRS) document, which serves as a medium to communicate user req...
Ishrar Hussain, Olga Ormandjieva, Leila Kosseim
CHI
2011
ACM
12 years 9 months ago
Skim reading by satisficing: evidence from eye tracking
Readers on the Web often skim through text to cope with the volume of available information. In a previous study [11] readers’ eye movements were tracked as they skimmed through...
Geoffrey B. Duggan, Stephen J. Payne
FLAIRS
2006
13 years 7 months ago
Evaluating WordNet Features in Text Classification Models
Incorporating semantic features from the WordNet lexical database is among one of the many approaches that have been tried to improve the predictive performance of text classifica...
Trevor N. Mansuy, Robert J. Hilderman