Self-Organizing Maps for cyclic and unbounded graphs

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.

• Type: Conference
• Year: 2008
• Where: ESANN
• Authors: Markus Hagenbuchner, Alessandro Sperduti, Ah Chung Tsoi
• Keywords: ESANN 2008, Graph Structured Information, Neural Networks, Positional Graphs, Self Organising Map