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» On Kernel Methods for Relational Learning
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AAAI
2006
14 years 11 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
15 years 1 months ago
Classification with Invariant Distance Substitution Kernels
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
Bernard Haasdonk, Hans Burkhardt
SEMWEB
2007
Springer
15 years 3 months ago
Learning Subsumption Relations with CSR: a Classification based Method for the Alignment of Ontologies
In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies" (CSR) method. Given a pair of concepts from two onto...
Vassilis Spiliopoulos, Alexandros G. Valarakos, Ge...
KDD
1994
ACM
140views Data Mining» more  KDD 1994»
15 years 1 months ago
A Comparison of Pruning Methods for Relational Concept Learning
Pre-Pruning and Post-Pruning are two standard methods of dealing with noise in concept learning. Pre-Pruning methods are very efficient, while Post-Pruning methods typically are m...
Johannes Fürnkranz
NIPS
2001
14 years 11 months ago
A kernel method for multi-labelled classification
This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems are usually decomposed into many two-class problems but the...
André Elisseeff, Jason Weston