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437
A survey on pagerank computing
 Internet Mathematics
, 2005
"... Abstract. This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. T ..."
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Cited by 106 (0 self)
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Abstract. This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component
TopicSensitive PageRank
, 2002
"... In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search resu ..."
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Cited by 543 (10 self)
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In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search
A uniform approach to accelerated pagerank computation
 In WWW
, 2005
"... In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain. Rather than communicate their current probability values to their neighbors at each step, nodes instead communicate only changes in probability va ..."
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Cited by 45 (0 self)
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In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain. Rather than communicate their current probability values to their neighbors at each step, nodes instead communicate only changes in probability
Bookmarkcoloring approach to personalized pagerank computing
 Internet Mathematics
, 2007
"... Below we introduce a novel bookmarkcoloring algorithm (BCA) that computes authority weights over the Web pages utilizing the Web hyperlink structure. The computed vector (BCV) is similar to the PageRank vector defined for a pagespecific teleportation. Meanwhile, BCA is very fast and BCV is sparse. ..."
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Cited by 20 (0 self)
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Below we introduce a novel bookmarkcoloring algorithm (BCA) that computes authority weights over the Web pages utilizing the Web hyperlink structure. The computed vector (BCV) is similar to the PageRank vector defined for a pagespecific teleportation. Meanwhile, BCA is very fast and BCV is sparse
PAGERANK COMPUTATION, WITH SPECIAL ATTENTION TO DANGLING NODES
"... Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the stochastic Google matrix G. The algorithm lumps all dangling nodes into a single node. We express lumping as a similarity transformation of G, and show that the PageRank of the nondangling nodes can b ..."
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Cited by 11 (0 self)
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Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the stochastic Google matrix G. The algorithm lumps all dangling nodes into a single node. We express lumping as a similarity transformation of G, and show that the PageRank of the nondangling nodes can
A sublinear time algorithm for pagerank computations
 In WAW
, 2012
"... Abstract. In a network, identifying all vertices whose PageRank is more than a given threshold value ∆ is a basic problem that has arisen in Web and social network analyses. In this paper, we develop a nearly optimal, sublinear time, randomized algorithm for a close variant of this problem. When giv ..."
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Cited by 9 (3 self)
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Abstract. In a network, identifying all vertices whose PageRank is more than a given threshold value ∆ is a basic problem that has arisen in Web and social network analyses. In this paper, we develop a nearly optimal, sublinear time, randomized algorithm for a close variant of this problem. When
Outlink Estimation or Pagerank Computation under Missing Data
 In: Alt. Track Papers and Posters Proc. 13th International World Wide Web Conference
, 2004
"... The enormity and rapid growth of the webgraph forces quantities such as its pagerank to be computed under missing information consisting of outlinks of pages that have not yet been crawled. This paper examines the role played by the size and distribution of this missing data in determining the accu ..."
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Cited by 5 (0 self)
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The enormity and rapid growth of the webgraph forces quantities such as its pagerank to be computed under missing information consisting of outlinks of pages that have not yet been crawled. This paper examines the role played by the size and distribution of this missing data in determining
The PageRank Citation Ranking: Bringing Order to the Web
 Stanford InfoLab
, 1999
"... The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively ..."
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Cited by 3269 (1 self)
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and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.
Distributed pagerank computation based on iterative aggregationdisaggregation methods
 Proceedings of the 14th ACM international conference on Information and knowledge management
, 2005
"... PageRank has been widely used as a major factor in search engine ranking systems. However, global link graph information is required when computing PageRank, which causes prohibitive communication cost to achieve accurate results in distributed solution. In this paper, we propose a distributed PageR ..."
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Cited by 15 (0 self)
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PageRank has been widely used as a major factor in search engine ranking systems. However, global link graph information is required when computing PageRank, which causes prohibitive communication cost to achieve accurate results in distributed solution. In this paper, we propose a distributed PageRank
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