Book ChapterDOI
Greedy approximation algorithms for finding dense components in a graph
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TLDR
This paper gives simple greedy approximation algorithms for these optimization problems of finding subgraphs maximizing these notions of density for undirected and directed graphs and answers an open question about the complexity of the optimization problem for directed graphs.Abstract:
We study the problem of finding highly connected subgraphs of undirected and directed graphs. For undirected graphs, the notion of density of a subgraph we use is the average degree of the subgraph. For directed graphs, a corresponding notion of density was introduced recently by Kannan and Vinay. This is designed to quantify highly connectedness of substructures in a sparse directed graph such as the web graph. We study the optimization problems of finding subgraphs maximizing these notions of density for undirected and directed graphs. This paper gives simple greedy approximation algorithms for these optimization problems. We also answer an open question about the complexity of the optimization problem for directed graphs.read more
Citations
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Scalable Motif-aware Graph Clustering
TL;DR: In this article, the authors developed new methods based on graph motifs for graph clustering, allowing more efficient detection of communities within networks, focusing on triangles within graphs but their techniques extend to other clique motifs as well.
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Evaluating Cooperation in Communities with the k-Core Structure
TL;DR: The k-core concept, which essentially measures the robustness of a community under degeneracy, is extended to weighted graphs, devising a novel concept of k-cores on weighted graphs and applied on large real world graphs -- such as DBLP and report interesting results.
Proceedings ArticleDOI
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling
TL;DR: This paper presents a sampling scheme that gives densest subgraph sparsifier, yielding a randomized algorithm that produces high-quality approximations while providing significant speedups and improved space complexity, and devise an exact algorithm that can treat both clique and biclique densities in a unified way.
Journal ArticleDOI
Pricing in vehicle sharing systems: optimization in queuing networks with product forms
TL;DR: A heuristic based on computing a Maximum Circulation on the demand graph together with a convex integer program solved optimally by a greedy algorithm is proposed and the performance ratio of this heuristic is proved to be exactly N/(N+M-1)$$N/(N-1).
References
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Proceedings ArticleDOI
Authoritative sources in a hyperlinked environment
TL;DR: This work proposes and test an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of \hub pages that join them together in the link structure, that has connections to the eigenvectors of certain matrices associated with the link graph.
Journal ArticleDOI
Trawling the Web for emerging cyber-communities
TL;DR: The subject of this paper is the systematic enumeration of over 100,000 emerging communities from a Web crawl, motivating a graph-theoretic approach to locating such communities, and describing the algorithms and algorithmic engineering necessary to find structures that subscribe to this notion.
Book ChapterDOI
The web as a graph: measurements, models, and methods
TL;DR: This paper describes two algorithms that operate on the Web graph, addressing problems from Web search and automatic community discovery, and proposes a new family of random graph models that point to a rich new sub-field of the study of random graphs, and raises questions about the analysis of graph algorithms on the Internet.
Proceedings ArticleDOI
Inferring Web communities from link topology
TL;DR: This investigation shows that although the process by which users of the Web create pages and links is very difficult to understand at a “local” level, it results in a much greater degree of orderly high-level structure than has typically been assumed.