Book ChapterDOI
Greedy approximation algorithms for finding dense components in a graph
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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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Proceedings ArticleDOI
Re-ranking of web image search results using a graph algorithm
TL;DR: The method re-ranks the results of text based systems by incorporating visual similarity of the resulting images by finding the densest component that corresponds to the largest set of most similar subset of images.
Proceedings ArticleDOI
Efficient Algorithms for Densest Subgraph Discovery on Large Directed Graphs
TL;DR: The notion of [ x, y]-core is introduced, which is a dense subgraph for G, and it is shown that the densest subgraph can be accurately located through the [x, y]core with theoretical guarantees.
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Scalable Betweenness Centrality Maximization via Sampling
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Spectral Properties of Hypergraph Laplacian and Approximation Algorithms
TL;DR: In this paper, a non-linear hypergraph Laplacian operator based on a diffusion process on the hypergraph is introduced, such that within each hyperedge, measure flows from vertices having maximum weighted measure to those having minimum.
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Protein complex prediction for large protein protein interaction networks with the Core&Peel method
TL;DR: The algorithm Core&Peel pushes forward the state-of-the-art in PPIN clustering providing an algorithmic solution with polynomial running time that attains experimentally demonstrable good output quality and speed on challenging large real networks.
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.