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» Learning Classifiers from Semantically Heterogeneous Data
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EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
CAISE
2006
Springer
13 years 11 months ago
An Infrastructure for Building Semantic Web Portals
One important task of semantic web portals is to offer both end users and applications a seamless access to knowledge contained in heterogeneous data sources in specific user commu...
Yuangui Lei, Vanessa Lopez, Enrico Motta
NIPS
2008
13 years 9 months ago
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Yi Zhang 0010, Jeff Schneider, Artur Dubrawski
IPM
2008
134views more  IPM 2008»
13 years 7 months ago
RSS: A framework enabling ranked search on the semantic web
The semantic web not only contains resources but also includes the heterogeneous relationships among them, which is sharply distinguished from the current web. As the growth of th...
Xiaomin Ning, Hai Jin, Hao Wu
JMLR
2010
185views more  JMLR 2010»
13 years 2 months ago
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Franz Pernkopf, Jeff A. Bilmes