Web Spam Detection by Probability Mapping GraphSOMs and Graph Neural Networks

  • Lucia Di Noi
  • Markus Hagenbuchner
  • Franco Scarselli
  • Ah Chung Tsoi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6353)


In this paper, we will apply, to the task of detecting web spam, a combination of the best of its breed algorithms for processing graph domain input data, namely, probability mapping graph self organizing maps and graph neural networks. The two connectionist models are organized into a layered architecture, consisting of a mixture of unsupervised and supervised learning methods. It is found that the results of this layered architecture approach are comparable to the best results obtained so far by others using very different approaches.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Lucia Di Noi
    • 1
  • Markus Hagenbuchner
    • 2
  • Franco Scarselli
    • 1
  • Ah Chung Tsoi
    • 3
  1. 1.University of SienaSienaItaly
  2. 2.University of WollongongWollongongAustralia
  3. 3.Hong Kong Baptist UniversityHong Kong

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