Publication | Open Access
Deeper Inside PageRank
901
Citations
98
References
2004
Year
Ranking AlgorithmEngineeringLearning To RankInside PagerankText MiningBasic Pagerank ModelComputational Social ScienceInformation RetrievalData ScienceData MiningSocial Network AnalysisComprehensive SurveyKnowledge DiscoverySocial RankingComputer ScienceSearch Engine DesignNetwork ScienceBusinessDeeper Inside PagerankSearch Engine Indexing
This paper serves as a companion or extension to the "Inside PageRank" paper by Bianchini et al. [Bianchini et al. 03]. It is a comprehensive survey of all issues associated with PageRank, covering the basic PageRank model, available and recommended solution methods, storage issues, existence, uniqueness, and convergence properties, possible alterations to the basic model, suggested alternatives to the traditional solution methods, sensitivity and conditioning, and finally the updating problem. We introduce a few new results, provide an extensive reference list, and speculate about exciting areas of future research.
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