《大数据分析与处理》课程资料 (1).pptxVIP

Analysis of Large Graphs:Link Analysis, PageRankNote to other teachers and users of these slides: We would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs. If you make use of a significant portion of these slides in your own lecture, please include this message, or a link to our web site: New Topic: Graph Data!High dim. dataLocality sensitive hashingClusteringDimensionality reductionGraph dataPageRank, SimRankCommunity DetectionSpam DetectionInfinite dataFiltering data streamsWeb advertisingQueries on streamsMachine learningSVMDecision TreesPerceptron, kNNAppsRecommender systemsAssociation RulesDuplicate document detection2 Graph Data: Social Networks3Facebook social graph4-degrees of separation [Backstrom-Boldi-Rosa-Ugander-Vigna, 2011] Graph Data: Media Networks4Connections between political blogsPolarization of the network [Adamic-Glance, 2005] Graph Data: Information Nets5Citation networks and Maps of science[B?rner et al., 2012] domain2domain1domain3routerInternetGraph Data: Communication Nets6 Graph Data: Technological Networks7Seven Bridges of K?nigsberg[Euler, 1735]Return to the starting point by traveling each link of the graph once and only once. Web as a GraphWeb as a directed graph:Nodes: WebpagesEdges: Hyperlinks8I teach a class on Networks.CS224W: Classes are in the Gates buildingComputer Science Department at StanfordStanford University Web as a GraphWeb as a directed graph:Nodes: WebpagesEdges: Hyperlinks9I teach a class on Networks.CS224W: Classes are in the Gates buildingComputer Science Department at StanfordStanford University Web as a Directed Graph10 Broad QuestionHow to organize the Web?First try: Human curatedWeb directoriesYahoo, DMOZ, LookSmartSecond try: Web SearchInformation Retrieval investigates:Find relevant docs in a small and trusted setNewspaper articles, Patents, etc.But: Web is huge, full of untrusted docum