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IJCAI
2003
13 years 7 months ago
Learning to Classify Texts Using Positive and Unlabeled Data
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
Xiaoli Li, Bing Liu
LRE
2008
110views more  LRE 2008»
13 years 5 months ago
Automatic building of an ontology on the basis of text corpora in Thai
This paper presents a methodology for automatic learning of ontologies from Thai text corpora, by extraction of terms and relations. A shallow parser is used to chunk texts on whic...
Aurawan Imsombut, Asanee Kawtrakul
SMC
2010
IEEE
186views Control Systems» more  SMC 2010»
13 years 4 months ago
Semantic enrichment of text representation with wikipedia for text classification
—Text classification is a widely studied topic in the area of machine learning. A number of techniques have been developed to represent and classify text documents. Most of the t...
Hiroki Yamakawa, Jing Peng, Anna Feldman
ACL
2012
11 years 8 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
AAAI
1998
13 years 7 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...