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» Using multiple ontologies in information extraction
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ICDCS
2002
IEEE
15 years 2 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
91
Voted
TIP
2008
107views more  TIP 2008»
14 years 9 months ago
Sampling-Based Correlation Estimation for Distributed Source Coding Under Rate and Complexity Constraints
In many practical distributed source coding (DSC) applications, correlation information has to be estimated at the encoder in order to determine the encoding rate. Coding efficien...
Ngai-Man Cheung, Huisheng Wang, Antonio Ortega
CIKM
2010
Springer
14 years 8 months ago
CiteData: a new multi-faceted dataset for evaluating personalized search performance
Personalized search systems have evolved to utilize heterogeneous features including document hyperlinks, category labels in various taxonomies and social tags in addition to free...
Abhay Harpale, Yiming Yang, Siddharth Gopal, Daqin...
IVC
2008
147views more  IVC 2008»
14 years 9 months ago
Distinctive and compact features
We consider the problem of extracting features for multi-class recognition problems. The features are required to make fine distinction between similar classes, combined with tole...
Ayelet Akselrod-Ballin, Shimon Ullman
ECCV
2004
Springer
15 years 11 months ago
Probabilistic Multi-view Correspondence in a Distributed Setting with No Central Server
Abstract. We present a probabilistic algorithm for finding correspondences across multiple images. The algorithm runs in a distributed setting, where each camera is attached to a s...
Shai Avidan, Yael Moses, Yoram Moses