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Advances in Social Network Mining and Analysis: Second by Brian Gallagher, Tina Eliassi-Rad (auth.), Lee Giles, Marc

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By Brian Gallagher, Tina Eliassi-Rad (auth.), Lee Giles, Marc Smith, John Yen, Haizheng Zhang (eds.)

This year’s quantity of Advances in Social community research comprises the p- ceedings for the second one overseas Workshop on Social community research (SNAKDD 2008). the yearly workshop co-locates with the ACM SIGKDD - ternational convention on wisdom Discovery and knowledge Mining (KDD). the second one SNAKDD workshop used to be held with KDD 2008 and bought greater than 32 submissions on social community mining and research subject matters. We permitted eleven normal papers and eight brief papers. Seven of the papers are integrated during this quantity. in recent times, social community learn has complicated signi?cantly, because of the superiority of the web social web content and speedy messaging platforms in addition to the provision of quite a few large-scale o?ine social community structures. those social community structures are typically characterised by way of the complicated community constructions and wealthy accompanying contextual info. Researchers are - creasingly attracted to addressing quite a lot of demanding situations living in those disparate social community structures, together with deciding on universal static topol- ical houses and dynamic houses through the formation and evolution of those social networks, and the way contextual info can assist in interpreting the pertaining socialnetworks.These matters haveimportant implications oncom- nitydiscovery,anomalydetection,trendpredictionandcanenhanceapplications in a number of domain names akin to info retrieval, advice platforms, - curity and so on.

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Extra info for Advances in Social Network Mining and Analysis: Second International Workshop, SNAKDD 2008, Las Vegas, NV, USA, August 24-27, 2008

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In HEP-TH, differential geometry papers tend to have higher clustering coefficient, but lower degree and betweenness than others topics. This indicates that differential geometry papers play a relatively isolated and peripheral role among high-energy physics papers, at least in our subset of the arXiv data. 6 Conclusion We examined the utility of label-independent features in the context of withinnetwork classification. Our experiments revealed a number of interesting findings: (1) LI features can make up for large amounts of missing class labels; (2) LI features can provide information above and beyond that provided by class labels alone; (3) the effectiveness of LI features is due, at least in part, to their consistency and their stabilizing effect on network classifiers; (4) no single label-independent feature dominates, and there is generally a benefit to combining a few diverse LI features.

Since an arbitrary element xi is γ-related to exactly k + 1 yj , σk (xi ) is distinguished as a named simplex. If we let d denote the maximum dimension of KX (γ, Y ), we immediately see that d ≤ m − 1. Let σ and τ be two simplices in KX (γ, Y ). , their intersection contains at least q + 1 elements. ) Then τ and σ are q-connected if there exists a sequence σ1 , σ2 , . . , σp of simplices in KX (γ, Y ), such that σ1 = σ and σp = τ and σi is q-near to σi+1 ∀1 ≤ i ≤ p − 1. Thus q-connectivity is the transitive closure of q-nearness.

Sci. USA 104, 36 (2007) 9. : Community detection using a measure of global influence. In: Proc. of the 2nd KDD Workshop on Social Network Analysis, SNAKDD 2008 (2008) 10. : Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA 99, 7821 (2002) 11. : Talk of the network: A complex systems look at the underlying process of word-of-mouth. Marketing Letters (2001) 12. : The strength of weak ties. The American Journal of Sociology (May 1973) 13. : A new status index derived from sociometric analysis.

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