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Mining of Massive Datasets - Stanford University

MiningofMassiveDatasetsJure LeskovecStanford RajaramanMilliway LabsJeffrey D. UllmanStanford 2010, 2011, 2012, 2013, 2014 Anand Rajaraman, Jure Leskovec,and Jeffrey D. UllmaniiPrefaceThis book evolved from material developed over several years by Anand Raja-raman and Jeff Ullman for a one-quarter course at Stanford . The courseCS345A, titled Web Mining , was designed as an advanced graduate course,although it has become accessible and interesting to advanced Jure Leskovec joined the Stanford faculty, we reorganizedthe materialconsiderably. He introduced a new course CS224W on network analysis andadded material to CS345A, which was renumbered CS246. The three authorsalso introduced a large-scale data - Mining project course, book nowcontains material taught in all three the Book Is AboutAt the highest level of description, this book is about data Mining .

examples are about the Web or data derived from the Web. Further, the book takes an algorithmic point of view: data mining is about applying algorithms to data, rather than using data to “train” a machine-learning engine of some sort. The principal topics covered are: 1. Distributed file systems and map-reduce as a tool for creating parallel

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