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SYNTHESE
2008
130views more  SYNTHESE 2008»
13 years 8 months ago
Appropriateness measures: an uncertainty model for vague concepts
Abstract We argue that in the decision making process required for selecting assertible vague descriptions of an object, it is practical that communicating agents adopt an epistemi...
Jonathan Lawry
SIGIR
2008
ACM
13 years 8 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
14 years 3 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
AAAI
2004
13 years 10 months ago
Text Classification by Labeling Words
Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
Bing Liu, Xiaoli Li, Wee Sun Lee, Philip S. Yu
IJACTAICIT
2010
200views more  IJACTAICIT 2010»
13 years 5 months ago
An Intelligent Framework for Natural Object Identification in Images
Human superiority over computers in identifying natural objects like clouds, water, grass etc. comes from two capabilities: the capability to maintain a growing knowledge base per...
Aasia Khanum