Triangular clustering in document networks
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If you have a question about this talk, please contact Eiko Yoneki.
Document networks have the characteristic that a document
node, e.g. a webpage or an article, carries meaningful content.
Properties of document networks are not only affected by topological
connectivity between nodes, but are also strongly influenced by the
semantic relation between the content of the nodes.We observed that
document networks have a large number of triangles and a high value
clustering coefficient.
Also there is a strong correlation between the probability of
formation of a triangle and the content similarity among the three
nodes involved. We propose the degree-similarity product (DSP)
model, which well reproduces these properties. The model achieves
this by using a preferential attachment mechanism that favours the
linkage between nodes that are both popular and similar.
This work is a step forward towards a better understanding of the
structure and evolution of document networks.
Paper link: http://www.iop.org/EJ/abstract/1367-2630/11/3/033019/
This talk is part of the Computer Laboratory Systems Research Group Seminar series.
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