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9,149
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.
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
Extrapolation Methods for Accelerating PageRank Computations
 In Proceedings of the Twelfth International World Wide Web Conference
, 2003
"... We present a novel algorithm for the fast computation of PageRank, a hyperlinkbased estimate of the "importance" of Web pages. The original PageRank algorithm uses the Power Method to compute successive iterates that converge to the principal eigenvector of the Markov matrix representing ..."
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Cited by 167 (12 self)
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We present a novel algorithm for the fast computation of PageRank, a hyperlinkbased estimate of the "importance" of Web pages. The original PageRank algorithm uses the Power Method to compute successive iterates that converge to the principal eigenvector of the Markov matrix representing
Experiments with PageRank computation
, 2004
"... PageRank algorithm is one of the most commonly used algorithms that determine the global importance of web pages. Due to the size of web graph which contains billions of nodes, computing a PageRank vector is very computational intensive and it may takes any time between months to hours depending on ..."
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Cited by 7 (0 self)
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PageRank algorithm is one of the most commonly used algorithms that determine the global importance of web pages. Due to the size of web graph which contains billions of nodes, computing a PageRank vector is very computational intensive and it may takes any time between months to hours depending
Rank Computation Methods for Web Documents
, 1999
"... We analyze the existing rank computation methods for the Web using a notion of rank flows and focusing on the methods for authority rank computation. We then propose a new model, called the voting model, for computing various ranks of Web pages that can be used by a search engine to better estimate ..."
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Cited by 1 (0 self)
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We analyze the existing rank computation methods for the Web using a notion of rank flows and focusing on the methods for authority rank computation. We then propose a new model, called the voting model, for computing various ranks of Web pages that can be used by a search engine to better estimate
Nonlinear Algorithms for StaticRank Computation
"... Mainstream linkbased staticrank algorithms (e.g. PageRank and its variants) express the importance of a page as the linear combination of its inlinks and compute page importance scores by solving a linear system in an iterative way. Such linear algorithms, however, may give apparently unreasonabl ..."
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Mainstream linkbased staticrank algorithms (e.g. PageRank and its variants) express the importance of a page as the linear combination of its inlinks and compute page importance scores by solving a linear system in an iterative way. Such linear algorithms, however, may give apparently
A comparative analysis of selection schemes used in genetic algorithms
 Foundations of Genetic Algorithms
, 1991
"... This paper considers a number of selection schemes commonly used in modern genetic algorithms. Specifically, proportionate reproduction, ranking selection, tournament selection, and Genitor (or «steady state") selection are compared on the basis of solutions to deterministic difference or d ..."
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Cited by 531 (31 self)
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This paper considers a number of selection schemes commonly used in modern genetic algorithms. Specifically, proportionate reproduction, ranking selection, tournament selection, and Genitor (or «steady state") selection are compared on the basis of solutions to deterministic difference
A Singular Value Thresholding Algorithm for Matrix Completion
, 2008
"... This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task of reco ..."
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Cited by 555 (22 self)
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This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task
Video google: A text retrieval approach to object matching in videos
 In ICCV
, 2003
"... We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, ill ..."
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Cited by 1636 (42 self)
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, illumination and partial occlusion. The temporal continuity of the video within a shot is used to track the regions in order to reject unstable regions and reduce the effects of noise in the descriptors. The analogy with text retrieval is in the implementation where matches on descriptors are precomputed
Muscle: multiple sequence alignment with high accuracy and high throughput
 NUCLEIC ACIDS RES
, 2004
"... We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent r ..."
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Cited by 2509 (7 self)
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We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using tree
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