Logo

Mining of Massive Datasets by Anand Rajaraman, Jeffrey D. Ullman

Small book cover: Mining of Massive Datasets

Mining of Massive Datasets
by

Publisher: Stanford University
Number of pages: 340

Description:
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.

Home page url

Download or read it online for free here:
Download link
(2MB, PDF)

Similar books

Book cover: Theory and Applications for Advanced Text MiningTheory and Applications for Advanced Text Mining
by - InTech
Text mining techniques are studied aggressively in order to extract the knowledge from the data. This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
(3395 views)
Book cover: Data-Intensive Text Processing with MapReduceData-Intensive Text Processing with MapReduce
by - Morgan & Claypool Publishers
This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns.
(4350 views)
Book cover: Foundations of DatabasesFoundations of Databases
by - Addison Wesley
This book provides in-depth coverage of the theory concerning the logical level of database management systems, including both classical and advanced topics. It includes detailed proofs and numerous examples and exercises.
(3928 views)
Book cover: Data Mining and Analysis: Fundamental Concepts and AlgorithmsData Mining and Analysis: Fundamental Concepts and Algorithms
by - Cambridge University Press
This textbook provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification.
(1423 views)