[PDF] Top 20 Community detection in sparse random networks

... . In ( Arias-Castro and Verzelen , 2012 ), we focused on the asymptotically dense regime where p 0 is large enough that np 0 > (n/N ) o(1) ...asymptotically sparse regime where p 0 is small enough that ... Voir le document complet

... spectral community detection matrix for sparse graphs. This is in fact a slight overstatement: as already observed in [20], as the graph under study gets sparser, D −1 A still possesses ... Voir le document complet

... node-centric, community detection problem (Clauset 2005; Chen et ...a community structure which is centered on one or few seed ...scenario in which computing a global community ... Voir le document complet

... for community detection on sparse graphs, as- suming here a more realistic setting where node degrees are ...proposed in the seminal work on the Bethe Hessian cluster- ing can be ameliorated ... Voir le document complet

... especially in social computing, one important aspect to consider is that we might often want to identify the personalized network of social contacts of interest to a single user ...local community ... Voir le document complet

... information in dynamic social networks, contextualizing community detection has been a challenging ...contextualized community detec- tion. In this work, we propose a temporal ... Voir le document complet

... of community detection in sparse networks, those with bounded average ...even in this regime, various natural semidefinite programs can be used to recover the community ... Voir le document complet

... events. In this paper, we present a method to detect anomalous network communications in IoT networks using a set of sparse ...of sparse autoencoders is then trained to learn the ... Voir le document complet

... of community detection in sparse dynamical graphs in which the community structure evolves over ...correlation in the class labels and in their temporal evolu- tion ... Voir le document complet

... Figure 3 shows the number of links as a function of (aggregated) extrinsic time in the Infocom 2006 network. We see that this network is very dynamic: there are many variations in the number of links. The ... Voir le document complet

... In this paper we propose a novel splitting and merging method for community detection in which a minimum spanning tree (MST) of dissimilarity between nodes in graph is emp[r] ... Voir le document complet

... Abstract—The problem of binary hypothesis testing is con- sidered when the measurements are drawn from a Markov random field (MRF) under each hypothesis. Spatial dependence of the measurements is incorporated by ... Voir le document complet

... topics in Q&A sites? Detecting interest groups can contribute to the question routing problem [3], which is very important in Q&A site ...the community management, for instance by allowing to ... Voir le document complet

... Another modification was suggested by Zhang [14] who claims that NMI is affected by systematic errors as a result of finite network size which may result in wrong conclusions when evaluating community ... Voir le document complet

... 5.3 Community detection method evaluation From an evaluation standpoint, community detection is a complex prob- ...presented in Section ...the community detection schemes ... Voir le document complet

... Clustering; Community detection; Random walks 1. INTRODUCTION Community detection is a fundamental problem in the field of graph mining, with applications to the analysis of ... Voir le document complet

... Another modification was suggested by Zhang [14] who claims that NMI is affected by systematic errors as a result of finite network size which may result in wrong conclusions when evaluating community ... Voir le document complet

... Terms— networks, community detection, spectral analy- sis, graphs, random ...INTRODUCTION In many real world networks representable through graphs, the nodes can be grouped into ... Voir le document complet

... However, in general they require explicit computation of the main eigenvectors of a suitable matrix (usually the Laplacian matrix of the ...initial random vector may, at least in some cases, provide ... Voir le document complet

... using random walk that is called walktrap clustering. It consists in assuming that a random walk starting from a vertex tends to stay in the community it belongs ...a random walk ... Voir le document complet