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» Extracting a Representation from Text for Semantic Analysis
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BPM
2009
Springer
168views Business» more  BPM 2009»
15 years 4 months ago
Divide-and-Conquer Strategies for Process Mining
The goal of Process Mining is to extract process models from logs of a system. Among the possible models to represent a process, Petri nets is an ideal candidate due to its graphic...
Josep Carmona, Jordi Cortadella, Michael Kishinevs...
EMNLP
2009
14 years 7 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
MM
2004
ACM
248views Multimedia» more  MM 2004»
15 years 3 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
IR
2010
14 years 8 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
SEMWEB
2009
Springer
15 years 4 months ago
TripleRank: Ranking Semantic Web Data by Tensor Decomposition
Abstract. The Semantic Web fosters novel applications targeting a more efficient and satisfying exploitation of the data available on the web, e.g. faceted browsing of linked open...
Thomas Franz, Antje Schultz, Sergej Sizov, Steffen...