Our goal is to find top-$k$ lists of nodes with the largest degrees in large complex networks quickly. If the adjacency list of the network is known (not often the case in complex networks), a deterministic algorithm to find the top-$k$ list of nodes with the largest degrees requires an average complexity of $\mathcal{O}(n)$ , where $n$ is the number of nodes in the network. Even this modest complexity can be very high for large complex networks. We propose to use a random-walk-based method. We show theoretically and by numerical experiments that for large networks, the random-walk method finds good-quality top lists of nodes with high probability and with computational savings of orders of magnitude. We also propose stopping criteria for t...
Mining frequent patterns in a single network (graph) poses a number of challenges. Already only to m...
In this paper we present a novel strategy to discover the community structure of (possibly, large) n...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...
Our goal is to find top-$k$ lists of nodes with the largest degrees in large complex networks quickl...
Our goal is to quickly find top k lists of nodes with the largest de-grees in large complex networks...
International audienceIn this paper, we address the problem of quick detection of high-degree entiti...
The article of record as published may be found at https://doi.org/10.1007/s13278-018-0520-3Identify...
Abstract The critical node detection problem (CNDP) aims to fragment a graph G=(V,E) b...
In this paper we address the problem of quick detection of high-degree entities in large online soci...
Centrality measures on networks can provide vital information such as the location of hubs in the ne...
With ever-growing popularity of social networks, web and bio-networks, mining large frequent pattern...
Similarity search is a fundamental problem in network analysis and can be applied in many applicatio...
Complex network theory crucially depends on the assumptions made about the degree distribution, whil...
Graphs are fundamental data structures and have been em-ployed for centuries to model real-world sys...
We initiate the study of local, sublinear time algorithms for finding vertices with extreme topologi...
Mining frequent patterns in a single network (graph) poses a number of challenges. Already only to m...
In this paper we present a novel strategy to discover the community structure of (possibly, large) n...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...
Our goal is to find top-$k$ lists of nodes with the largest degrees in large complex networks quickl...
Our goal is to quickly find top k lists of nodes with the largest de-grees in large complex networks...
International audienceIn this paper, we address the problem of quick detection of high-degree entiti...
The article of record as published may be found at https://doi.org/10.1007/s13278-018-0520-3Identify...
Abstract The critical node detection problem (CNDP) aims to fragment a graph G=(V,E) b...
In this paper we address the problem of quick detection of high-degree entities in large online soci...
Centrality measures on networks can provide vital information such as the location of hubs in the ne...
With ever-growing popularity of social networks, web and bio-networks, mining large frequent pattern...
Similarity search is a fundamental problem in network analysis and can be applied in many applicatio...
Complex network theory crucially depends on the assumptions made about the degree distribution, whil...
Graphs are fundamental data structures and have been em-ployed for centuries to model real-world sys...
We initiate the study of local, sublinear time algorithms for finding vertices with extreme topologi...
Mining frequent patterns in a single network (graph) poses a number of challenges. Already only to m...
In this paper we present a novel strategy to discover the community structure of (possibly, large) n...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...