The Connectivity Server: fast access to linkage information on the Web

Bharat, Krishna; Bröder, Arndt; Henzinger, Monika; Kumar, Puneet; Venkatasubramanian, Suresh

doi:10.1016/s0169-7552(98)80047-0

Cited by 116 publications

(86 citation statements)

References 6 publications

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“…In Section 8 we mentioned systems for compiling high-quality www resource lists that have been built using extensions to the algorithms developed here; see Bharat and Henzinger [6] and Chakrabarti et al [10,11]. The implementation of the Bharat-Henzinger system made use of the recently developed Connectivity Server (Bharat et al [5]), which provides very efficient retrieval for linkage information contained in the AltaVista index.…”

Section: Resultsmentioning

confidence: 99%

Authoritative Sources in a Hyperlinked Environment

Kleinberg¹

2011

The Structure and Dynamics of Networks

1,436

2,017

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The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of contexts on the World Wide Web. The central issue we address within our framework is the distillation of broad search topics, through the discovery of "authoritative" information sources on such topics. We propose 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. Our formulation has connections to the eigenvectors of certain matrices associated with the link graph; these connections in turn motivate additional heuristics for link-based analysis.

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Section: Resultsmentioning

confidence: 99%

Authoritative Sources in a Hyperlinked Environment

Kleinberg¹

2011

The Structure and Dynamics of Networks

1,436

2,017

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“…The WebGraph compression method is indeed the most successful member of a family of approaches to compress Web graphs based on their statistical properties [5,7,1,23,21,20]. It allows fast extraction of the neighbors of a page while spending just a few bits per link (about 2 to 6, depending on the desired navigation performance).…”

Section: Introductionmentioning

confidence: 99%

k2-Trees for Compact Web Graph Representation

Brisaboa

Ladra

Navarro

2009

Lecture Notes in Computer Science

106

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Abstract. This paper presents a Web graph representation based on a compact tree structure that takes advantage of large empty areas of the adjacency matrix of the graph. Our results show that our method is competitive with the best alternatives in the literature, offering a very good compression ratio (3.3-5.3 bits per link) while permitting fast navigation on the graph to obtain direct as well as reverse neighbors (2-15 microseconds per neighbor delivered). Moreover, it allows for extended functionality not usually considered in compressed graph representations.

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“…It is easy to verify that (MM T ) ij is the number of nodes that both i and j have outedges to. The matrix (MM T ) can be computed in time O ( P n i=1 t G W (i) 2 ), assuming that we compute a list of the non-zero entries of (MM T ). We also compute an array R, where R j] = out-deg(j).…”

Section: A Baseline Hu Man-based Schemementioning

confidence: 99%

“…cost(i; j) < cost(i; r)g and the set of edges from every other vertex to r. This also gives us the weight of each edge in G S . Since there can be at most P n i=1 t G W (i) 2 nonzero entries in (MM T ), the total time required to compute the graph G S is O (n + P n i=1 t G W (i) 2 ).…”

Section: A Baseline Hu Man-based Schemementioning

confidence: 99%

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Towards compressing Web graphs

Adler

Mitzenmacher

Proceedings DCC 2001. Data Compression Conference

148

113

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In this paper, we consider the problem of compressing graphs of the link structure of the World Wide Web. We provide e cient algorithms for such compression that are motivated by recently proposed random graph models for describing the Web. The algorithms are based on reducing the compression problem to the problem of nding a minimum spanning tree in a directed graph related to the original link graph. The performance of the algorithms on graphs generated by the random graph models suggests that by taking advantage of the link structure of the Web, one may achieve signi cantly better compression than natural Hu man-based schemes. We also provide hardness results demonstrating limitations on natural extensions of our approach.

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The Connectivity Server: fast access to linkage information on the Web

Cited by 116 publications

References 6 publications

Authoritative Sources in a Hyperlinked Environment

Authoritative Sources in a Hyperlinked Environment

k2-Trees for Compact Web Graph Representation

Towards compressing Web graphs

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