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» Classifying Documents Without Labels
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SIGIR
2006
ACM
14 years 3 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
DAGSTUHL
2007
13 years 11 months ago
Multi-Aspect Tagging for Collaborative Structuring
Local tag structures have become frequent through Web 2.0: Users "tag" their data without specifying the underlying semantics. Every user annotates items in an individual...
Katharina Morik, Michael Wurst
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 10 months ago
Mining social networks for personalized email prioritization
Email is one of the most prevalent communication tools today, and solving the email overload problem is pressingly urgent. A good way to alleviate email overload is to automatical...
Shinjae Yoo, Yiming Yang, Frank Lin, Il-Chul Moon
WWW
2010
ACM
14 years 4 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
SIGIR
2003
ACM
14 years 3 months ago
Table extraction using conditional random fields
The ability to find tables and extract information from them is a necessary component of data mining, question answering, and other information retrieval tasks. Documents often c...
David Pinto, Andrew McCallum, Xing Wei, W. Bruce C...