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  VoG: Summarizing and Understanding Large Graphs

Koutra, D., Kang, U., Vreeken, J., & Faloutsos, C. (2014). VoG: Summarizing and Understanding Large Graphs. Retrieved from http://arxiv.org/abs/1406.3411.

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Latex : {VoG}: {Summarizing} and Understanding Large Graphs

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arXiv:1406.3411.pdf (Preprint), 2MB
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 Creators:
Koutra, Danai1, Author
Kang, U1, Author
Vreeken, Jilles2, Author           
Faloutsos, Christos1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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Free keywords: cs.SI, Physics, Physics and Society, physics.soc-ph
 Abstract: How can we succinctly describe a million-node graph with a few simple sentences? How can we measure the "importance" of a set of discovered subgraphs in a large graph? These are exactly the problems we focus on. Our main ideas are to construct a "vocabulary" of subgraph-types that often occur in real graphs (e.g., stars, cliques, chains), and from a set of subgraphs, find the most succinct description of a graph in terms of this vocabulary. We measure success in a well-founded way by means of the Minimum Description Length (MDL) principle: a subgraph is included in the summary if it decreases the total description length of the graph. Our contributions are three-fold: (a) formulation: we provide a principled encoding scheme to choose vocabulary subgraphs; (b) algorithm: we develop \method, an efficient method to minimize the description cost, and (c) applicability: we report experimental results on multi-million-edge real graphs, including Flickr and the Notre Dame web graph.

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Language(s): eng - English
 Dates: 2014-06-122014
 Publication Status: Published online
 Pages: 13 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1406.3411
URI: http://arxiv.org/abs/1406.3411
BibTex Citekey: KoutraKangVreekenFaloutsosarXiv2014
 Degree: -

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