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Directed Laplacian Kernels for Link Analysis.
- Source :
- Intelligent Data Engineering & Automated Learning - IDEAL 2006; 2006, p314-321, 8p
- Publication Year :
- 2006
-
Abstract
- Application of kernel methods to link analysis is presented. Novel kernels based on directed graph Laplacians are proposed and their application as measures of relatedness between nodes in a directed graph is presented. The kernels express relatedness and take into account the global importance of the nodes in a citation graph. Limitations of existing kernels are given with a discussion how they are addressed by directed Laplacian kernels. Links between the kernels and PageRank ranking algorithm are also presented. The proposed kernels are evaluated on a dataset of scientific bibliographic citations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540454854
- Database :
- Complementary Index
- Journal :
- Intelligent Data Engineering & Automated Learning - IDEAL 2006
- Publication Type :
- Book
- Accession number :
- 32914167
- Full Text :
- https://doi.org/10.1007/11875581_38