A Hypergraph-Based Model for Graph Clustering: Application to Image Indexing

  • Salim Jouili
  • Salvatore Tabbone
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5702)


In this paper, we introduce a prototype-based clustering algorithm dealing with graphs. We propose a hypergraph-based model for graph data sets by allowing clusters overlapping. More precisely, in this representation one graph can be assigned to more than one cluster. Using the concept of the graph median and a given threshold, the proposed algorithm detects automatically the number of classes in the graph database. We consider clusters as hyperedges in our hypergraph model and we define a retrieval technique indexing the database with hyperedge centroids. This model is interesting to travel the data set and efficient to cluster and retrieve graphs.


Rand Index Graph Cluster Graph Database Graph Query Median Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Salim Jouili
    • 1
  • Salvatore Tabbone
    • 1
  1. 1.LORIA UMR 7503University of Nancy 2Vandoeuvre-lès-Nancy CedexFrance

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