Overlapping community search in very large graphs
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099.1/13770
Tipus de documentProjecte Final de Màster Oficial
Data2010-01
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The main objective of the thesis is the creation of an algorithm to detect
the community structure of large graphs, allowing for nestings and overlappings.
Although it has been shown that communities are usually overlapping
and hierarchical, we must stress that most of the literature related to community
search has focused on nding partitions of the graph. In addition,
given the size of modern data sets, most of them typically rely on prohibitively
expensive computations.
We will propose the algorithm OCA, an algorithm for community detection
with nestings and overlaps. It has been able to run in the larger
datasets of which we are aware. Our algorithm neither requires the user to
set non-intuitive parameters in order to get good results, nor to preassume
a certain size or number for the communities, since they are found naturally
from the graph structure.
The core of the algorithm relies on the de nition of a new tness function
that allows to evaluate the quality of a community naturally including those
nodes shared by other communities.
TitulacióMÀSTER UNIVERSITARI EN MATEMÀTICA APLICADA (Pla 2009)
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
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memoria.pdf | 1,698Mb | Visualitza/Obre |