Publication | Closed Access
Tracking the random surfer
54
Citations
22
References
2010
Year
Unknown Venue
Ranking AlgorithmTeleportation ParameterEngineeringField RoboticsLearning To RankNetwork AnalysisWeb AnalyticsText MiningComputational Social ScienceInformation RetrievalData ScienceObject TrackingStatisticsSocial Network AnalysisMachine VisionKnowledge DiscoveryWebometricsMoving Object TrackingComputer ScienceRandom SurferSearch Engine DesignSignal ProcessingNetwork ScienceRandom Surfer ModelEye TrackingBusinessConstant Teleportation ParameterTracking System
PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models the probability of following an edge inside the graph or, when the graph comes from a network of web pages and links, clicking a link on a web page. We empirically measure the teleportation parameter based on browser toolbar logs and a click trail analysis. For a particular user or machine, such analysis produces a value of alpha. We find that these values nicely fit a Beta distribution with mean edge-following probability between 0.3 and 0.7, depending on the site. Using these distributions, we compute PageRank scores where PageRank is computed with respect to a distribution as the teleportation parameter, rather than a constant teleportation parameter. These new metrics are evaluated on the graph of pages in Wikipedia.
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