A Scalable Kernel Approach to Learning in Semantic Graphs with Applications to Linked Data

In this paper we discuss a kernel approach to learning in semantic graphs. To scale up the performance to large data sets, we employ the Nystr öm approximation. We derive a kernel derived from semantic relations in a local neighborhood of a node. One can apply our approach to problems in multi-relational domains with several thousand graph nodes and more than a million potential links. We apply the approach to DBpedia data extracted from the RDF-graph of the Semantic Web’s Linked Open Data (LOD).

[1]  Christopher K. I. Williams,et al.  Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.

[2]  Ben Taskar,et al.  Link Prediction in Relational Data , 2003, NIPS.

[3]  Thomas Gärtner,et al.  Kernels and Distances for Structured Data , 2004, Machine Learning.

[4]  Ellen M. Voorhees,et al.  Retrieval evaluation with incomplete information , 2004, SIGIR '04.

[5]  Xiaojin Zhu,et al.  Semi-Supervised Learning Literature Survey , 2005 .

[6]  Stephen Muggleton,et al.  Support Vector Inductive Logic Programming , 2005, Discovery Science.

[7]  Wei Chu,et al.  Stochastic Relational Models for Discriminative Link Prediction , 2006, NIPS.

[8]  Simone Paolo Ponzetto,et al.  WikiRelate! Computing Semantic Relatedness Using Wikipedia , 2006, AAAI.

[9]  Luc De Raedt,et al.  kFOIL: Learning Simple Relational Kernels , 2006, AAAI.

[10]  Gerhard Weikum,et al.  WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .

[11]  S. V. N. Vishwanathan,et al.  Graph kernels , 2007 .

[12]  Jens Lehmann,et al.  DBpedia: A Nucleus for a Web of Open Data , 2007, ISWC/ASWC.

[13]  Nicola Fanizzi,et al.  Non-parametric Statistical Learning Methods for Inductive Classifiers in Semantic Knowledge Bases , 2008, 2008 IEEE International Conference on Semantic Computing.

[14]  Achim Rettinger,et al.  Towards Machine Learning on the Semantic Web , 2008, URSW.

[15]  Kristian Kersting,et al.  Multi-Relational Learning with Gaussian Processes , 2009, IJCAI.

[16]  Jeff Z. Pan,et al.  Resource Description Framework , 2020, Definitions.

[17]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[18]  Achim Rettinger,et al.  Materializing and Querying Learned Knowledge , 2009 .