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RNTI

MODULAD
Graph Aggregation : Application to Social Networks
In HDSDA 2013, vol. RNTI-E-25, pp.157-177
Résumé
In the enterprise context, people need to exploit and mainly visualize
different types of interactions between heterogeneous objects. Graph model
seems to be the most appropriate way to represent those interactions. However,
the extracted graphs have in general a huge size which makes it difficult to analyze
and visualize. An aggregation step is needed to have more understandable
graphs in order to allow users discovering underlying information and hidden
relationships between entities. In this work, we propose new measures to evaluate
the quality of summaries based on an existing algorithm named k-SNAP that
produces a summarized graph according to user-selected node attributes and relationships.