Random Walks and Diffusions on Graphs and Databases

Blanchard, Philippe; Volchenkov, Dimitri

doi:10.1007/978-3-642-19592-1

Cited by 64 publications

(48 citation statements)

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Order By: Relevance

“…In this case, the order parameter would be non vanishing only on an infinitesimal fraction of the network and, therefore, it is not possible to speak of a true phase transition at β c determined by Eq. (202). Finally, for annealed networks which rewire their connections on the same time scale of the dynamical process and keep their degree sequence constant, one can approximate r ij as r ij = ⟨a ij ⟩ = k i k j ⟨k⟩ .…”

Section: Disease Spreading On Single-layer Networkmentioning

confidence: 99%

The structure and dynamics of multilayer networks

et al. 2014

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In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal-or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.

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Section: Disease Spreading On Single-layer Networkmentioning

confidence: 99%

The structure and dynamics of multilayer networks

et al. 2014

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“…In the following we provide a short summary that highlights the important properties of this process. Note that these are facts already known from the theory of random walks on single layer networks [8,19], but later on we will extend this framework to multi-layer networks.…”

Section: Methods and Definitionsmentioning

confidence: 92%

An Ensemble Perspective on Multi-layer Networks

Wider

Garas

Scholtes

et al. 2016

Understanding Complex Systems

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We study properties of multi-layered, interconnected networks from an ensemble perspective, i.e. we analyze ensembles of multi-layer networks that share similar aggregate characteristics. Using a diffusive process that evolves on a multi-layer network, we analyze how the speed of diffusion depends on the aggregate characteristics of both intra-and inter-layer connectivity. Through a block-matrix model representing the distinct layers, we construct transition matrices of random walkers on multi-layer networks, and estimate expected properties of multi-layer networks using a mean-field approach. In addition, we quantify and explore conditions on the link topology that allow to estimate the ensemble average by only considering aggregate statistics of the layers. Our approach can be used when only partial information is available, like it is usually the case for real-world multi-layer complex systems.

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“…Since our graph G is a connected, non-bipartite, and undirected graph, it can be shown that the markov chain over it is irreducible and aperiodic [2]. Thus, by the PerronFrobenius theorem [7], it is clear that the random walk on G will converge to a stationary state which corresponds to the left eigenvector of the stochastic matrix.…”

Section: Random Walk Based Algorithm For Reviewer Recommendationmentioning

confidence: 97%

Patch Reviewer Recommendation in OSS Projects

Lee

Ihara

Monden

et al. 2013

2013 20th Asia-Pacific Software Engineering Conference (APSEC)

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In an Open Source Software (OSS) project, many developers contribute by submitting source code patches. To maintain the quality of the code, certain experienced developers review each patch before it can be applied or committed. Ideally, within a short amount of time after its submission, a patch is assigned to a reviewer and reviewed. In the real world, however, many large and active OSS projects evolve at a rapid pace and the core developers can get swamped with a large number of patches to review. Furthermore, since these core members may not always be available or may choose to leave the project, it can be challenging, at times, to find a good reviewer for a patch. In this paper, we propose a graphbased method to automatically recommend the most suitable reviewers for a patch. To evaluate our method, we conducted experiments to predict the developers who will apply new changes to the source code in the Eclipse project. Our method achieved an average recall of 0.84 for top-5 predictions and a recall of 0.94 for top-10 predictions.

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Random Walks and Diffusions on Graphs and Databases

Cited by 64 publications

References 0 publications

The structure and dynamics of multilayer networks

The structure and dynamics of multilayer networks

An Ensemble Perspective on Multi-layer Networks

Patch Reviewer Recommendation in OSS Projects

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