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Self-organizing maps for cyclic and unbounded graphs

Conference Paper


Abstract


  • This paper introduces a new concept to the processing of graph structured information using self organising map framework. Previous approaches to this problem were limited to the processing of bounded graphs. The computational complexity of such methods grows rapidly with the level of connectivity, and are restricted to the processing of positional graphs. The concept proposed in this paper addresses these issues by reducing the computational demand, and by allowing the processing of non-positional graphs. This is achieved by utilising the state space of the self organising map instead of the states of the nodes in the graph for processing.

Publication Date


  • 2008

Citation


  • Hagenbuchner, M., Sperduti, A. & Tsoi, A. (2008). Self-organizing maps for cyclic and unbounded graphs. ESANN 2008 Proceedings. European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (pp. 203-208). Bruges, Belgium: ESANN.

Scopus Eid


  • 2-s2.0-61849163336

Start Page


  • 203

End Page


  • 208

Abstract


  • This paper introduces a new concept to the processing of graph structured information using self organising map framework. Previous approaches to this problem were limited to the processing of bounded graphs. The computational complexity of such methods grows rapidly with the level of connectivity, and are restricted to the processing of positional graphs. The concept proposed in this paper addresses these issues by reducing the computational demand, and by allowing the processing of non-positional graphs. This is achieved by utilising the state space of the self organising map instead of the states of the nodes in the graph for processing.

Publication Date


  • 2008

Citation


  • Hagenbuchner, M., Sperduti, A. & Tsoi, A. (2008). Self-organizing maps for cyclic and unbounded graphs. ESANN 2008 Proceedings. European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (pp. 203-208). Bruges, Belgium: ESANN.

Scopus Eid


  • 2-s2.0-61849163336

Start Page


  • 203

End Page


  • 208