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» Ontologies Improve Text Document Clustering
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KCAP
2011
ACM
12 years 10 months ago
Eliciting hierarchical structures from enumerative structures for ontology learning
Some discourse structures such as enumerative structures have typographical, punctuational and laying out characteristics which (1) make them easily identifiable and (2) convey hi...
Mouna Kamel, Bernard Rothenburger
NIPS
2008
13 years 9 months ago
Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
Liu Yang, Rong Jin, Rahul Sukthankar
ICDAR
1995
IEEE
13 years 11 months ago
Visual inter-word relations and their use in OCR postprocessing
A technique is presented that uses visual relationships between word images in a document to improve the recognition of the text it contains. This technique takes advantage of the...
Tao Hong, Jonathan J. Hull
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
14 years 1 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
LREC
2010
138views Education» more  LREC 2010»
13 years 9 months ago
Evaluating a Text Mining Based Educational Search Portal
In this paper, we present the main features of a text mining based search engine for the UK Educational Evidence Portal available at the UK National Centre for Text Mining (NaCTeM...
Sophia Ananiadou, John McNaught, James Thomas, Mar...