Graph Mining and Graph Kernels

  • Borgwardt K
  • Yan X
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Abstract

Social and biological networks have led to a huge interest in dataanalysis on graphs. Various groups within the {KDD} community havebegun to study the task of data mining on graphs, including researchersfrom database-oriented graph mining, and researchers from kernelmachine learning. Their approaches are often complementary, and wefeel that exciting research problems and techniques can be discoveredby exploring the link between these different approaches to graphmining.This tutorial presents a comprehensive overview of the techniquesdeveloped in graph mining and graph kernels and examines the connectionbetween them. The goal of this tutorial is i) to introduce newcomersto the field of graph mining, ii) to introduce people with databasebackground to graph mining using kernel machines, iii) to introducepeople with machine learning background to database-oriented graphmining, and iv) to present exciting research problems at the interfaceof both fields.

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APA

Borgwardt, K. M., & Yan, X. (2008). Graph Mining and Graph Kernels. Association for Computing Machinery (ACM). https://doi.org/10.1145/1401890.1551565

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