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  Metropolis Algorithms for Representative Subgraph Sampling

Hübler, C., Kriegel H-P, Borgwardt, K., & Ghahramani, Z. (2008). Metropolis Algorithms for Representative Subgraph Sampling. In Eighth IEEE International Conference on Data Mining (ICDM '08) (pp. 283-292). Piscataway, NJ, USA: IEEE.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C637-C Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C638-A
Genre: Konferenzbeitrag

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 Urheber:
Hübler, C, Autor
Kriegel H-P, Borgwardt, K1, Autor           
Ghahramani, Z, Autor
Giannotti, F., Herausgeber
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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Schlagwörter: -
 Zusammenfassung: While data mining in chemoinformatics studied graph data with dozens of nodes, systems biology and the Internet are now generating graph data with thousands and millions of nodes. Hence data mining faces the algorithmic challenge of coping with this significant increase in graph size: Classic algorithms for data analysis are often too expensive and too slow on large graphs. While one strategy to overcome this problem is to design novel efficient algorithms, the other is to 'reduce' the size of the large graph by sampling. This is the scope of this paper: We will present novel Metropolis algorithms for sampling a 'representative' small subgraph from the original large graph, with 'representative' describing the requirement that the sample shall preserve crucial graph properties of the original graph. In our experiments, we improve over the pioneering work of Leskovec and Faloutsos (KDD 2006), by producing representative subgraph samples that are both smaller and of higher quality than those produced by other methods from the literature.

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Sprache(n):
 Datum: 2008-12
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISBN: 978-0-7695-3502-9
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4781123tag=1
DOI: 10.1109/ICDM.2008.124
BibTex Citekey: HublerKBG2008
 Art des Abschluß: -

Veranstaltung

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Titel: Eighth IEEE International Conference on Data Mining (ICDM '08)
Veranstaltungsort: Pisa, Italy
Start-/Enddatum: -

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Titel: Eighth IEEE International Conference on Data Mining (ICDM '08)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Piscataway, NJ, USA : IEEE
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 283 - 292 Identifikator: -