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Τίτλος:
"Degeneracy based graph mining methods for community evaluation" - Μιχάλης Βαζιργιάννης
Πότε:
24.10.2012 - 24.10.2012 11.00 h - 12.00 h
Πού:
Αίθουσα Εκδηλώσεων, Κεντρικό Κτήριο - Μαρούσι
Κατηγορία:
Παρουσιάσεις - Ομιλίες

Περιγραφή

Τίτλος: "Degeneracy based graph mining methods for community evaluation"

Μιχάλης Βαζιργιάννης

Περίληψη 

Graphs constitute the dominant data structure in the  web graph, social networks, protein interaction networks, terms dependency graphs etc. Important knowledge is hidden in the macroscopic topology and features of these graphs. The dominant knowledge artifacts extracted from graphs are either individual node based scores (such as authority/hubness/centrality) or unsupervised grouping of nodes in to clusters or global statistics computations (such as degree distributions etc). What is missing is metrics, structures and measures that represent the deeper knowledge hidden in the macroscopic structure of potentially directed/weighted graphs.

We propose new metrics and evaluation schemes for the macroscopic structure of graphs capitalizing on the degeneracy concept, i.e. k-cores, towards identifying the most cohesive components of graphs – finding thus the most collaborative constituents. These metrics compute the most robust subgraphs representing dense and mutual connectivity in the case of directed and weighted graphs as well. Connectivity can be then interpreted in several ways: i.e. as collaboration in citation or social networking graphs, collective affinity in protein interaction graphs etc. We further extend k-core to deal with directed graphs, introducing the D-core concept, as means of evaluating a digraph’s collaborative nature. Based on the D-core we devise a wealth of novel metrics used to evaluate the graphs collaboration features. We applied the above approaches on large real world graphs - Wikipedia and DBLP - and report interesting results. Further more we extend the k-core structure to cover the case of signed graphs – with interesting applications in trust networks.

We conducted experiments on real (DBLP, Wikipedia, slashdot) and synthetic data sets. The results are interesting and give rise for novel metrics for community evaluation.


Βιογραφικό

http://www.db-net.aueb.gr/michalis/

 
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Τόπος διεξαγωγής

Χώρος:
Αίθουσα Εκδηλώσεων, Κεντρικό Κτήριο
Οδός:
Αρτέμιδος 6 & Επιδαύρου
ΤΚ:
15125
Πόλη:
Μαρούσι
Χώρα:
Χώρα: gr

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