Goodreads helps you keep track of books you want to read.
Start by marking “Mining of Massive Datasets” as Want to Read:
Mining of Massive Datasets
Enlarge cover
Rate this book
Clear rating
Open Preview

Mining of Massive Datasets

4.41  ·  Rating Details  ·  119 Ratings  ·  9 Reviews
The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for para ...more
Hardcover, 326 pages
Published December 30th 2011 by Cambridge University Press (first published October 27th 2011)
More Details... edit details

Friend Reviews

To see what your friends thought of this book, please sign up.

Reader Q&A

To ask other readers questions about Mining of Massive Datasets, please sign up.

Be the first to ask a question about Mining of Massive Datasets

This book is not yet featured on Listopia. Add this book to your favorite list »

Community Reviews

(showing 1-30 of 544)
filter  |  sort: default (?)  |  Rating Details
Ben Haley
Oct 31, 2011 Ben Haley rated it it was amazing
The mining of massive datasets a clear, practical, and studied exploration of how to extract meaning from huge datasets (Terabytes, Exabytes, Petabytes oh my). I recommend the free version.

The book uses practical examples including spam email, google's page rank, and netflix's recommendation service to explore the algorithms necessary to process huge data on infrastructures like map reduce.

The authors have the necessary experience to define the field. Ullman is the powerhouse behind several ven
Natalia Shakhalova
This is a text book for Mining of Massive Datasets course at Stanford. Was very helpful when taking this course at Coursera. It describes different aspects of the domain and the theory behind existing solutions (search engines, networks analysis, recommender systems, online algorithms). It keeps a good balance of strict mathematical theory with all the proofs and references to its practical applications in modern systems. Wide variety of algorithms and ideas for applications in different domains ...more
Yasiru (reviews will soon be removed and linked to blog)
There's an up-to-date free version at and a full-fledged Stanford MOOC on Coursera. I took the course initially without much reference to the text, but while the lectures were excellent (and the whole course one of the best I've taken on the platform) I wish I'd had more time to go through the book first.
Aug 06, 2013 Shane rated it really liked it
This is more what I was looking for with the other "Big Data" book I read.
Although, this is quite a bit over my head, and more positioned at college study.

I expect this is something I will reference back to later. I read the "free" pdf version, but I'd like to have a copy of the updated version when it becomes available.
Akash Goel
Nov 18, 2015 Akash Goel rated it really liked it
This book is definitely a great companion of the Coursera MMDS class. But it lacks a few things, such as proper introductions and a natural information flow. Good for quick reference and examples, not too great to study or understand in depth.
Dec 20, 2014 Kjn rated it it was amazing
I got a lot from this and that was surprising as I had already read some books here. The nicest part is the Locally Sensitive Hashing.

This is just very good quality. Quite a bit of ideas you can use in your practise.
Sep 14, 2015 Victor rated it it was amazing
Shelves: a-i, computer-science
I skimmed this book to decide whether to enroll on the Stanford course with the same name, definitely I will enroll on the next available session, very interesting stuff about squeezing information from big data sets
Apr 27, 2015 Bryan rated it really liked it
It is a text book. It is a good book for the topic. Not much to say here.
Chitrank Dixit
Chitrank Dixit marked it as to-read
Jun 23, 2016
Arturo Pina
Arturo Pina marked it as to-read
Jun 22, 2016
Murilo Andrade
Murilo Andrade marked it as to-read
Jun 21, 2016
Bibliophage rated it it was amazing
Jun 18, 2016
Monika is currently reading it
Jun 18, 2016
Sam rated it really liked it
Jun 17, 2016
Greg Samek
Greg Samek marked it as to-read
Jun 17, 2016
Modiga Phemelo
Modiga Phemelo marked it as to-read
Jun 16, 2016
Stanley marked it as to-read
Jun 13, 2016
joseph teresi jr
joseph teresi jr marked it as to-read
Jun 07, 2016
John Shuck
John Shuck marked it as to-read
Jun 05, 2016
Alastair Kemp
Alastair Kemp marked it as to-read
Jun 05, 2016
Ignas marked it as to-read
Jun 01, 2016
Misha Veldhoen
Misha Veldhoen marked it as to-read
May 25, 2016
Sergio Felperin
Sergio Felperin is currently reading it
May 24, 2016
Mogie marked it as to-read
May 21, 2016
Sushant Kadam
Sushant Kadam marked it as to-read
May 21, 2016
Umesh Bhat
Umesh Bhat marked it as to-read
May 18, 2016
Tony Gu
Tony Gu marked it as to-read
May 17, 2016
« previous 1 3 4 5 6 7 8 9 18 19 next »
There are no discussion topics on this book yet. Be the first to start one »
  • Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
  • Introduction to Information Retrieval
  • Bayesian Reasoning and Machine Learning
  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  • Hadoop: The Definitive Guide
  • Pattern Recognition and Machine Learning
  • Natural Language Processing with Python
  • Information Theory, Inference and Learning Algorithms
  • Taming Text
  • Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
  • MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems
  • Machine Learning in Action
  • Big Data
  • Learning Spark
  • Machine Learning for Hackers
  • Hadoop in Action
  • Machine Learning: An Algorithmic Perspective
  • Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology

Goodreads is hiring!

If you like books and love to build cool products, we may be looking for you.
Learn more »

Share This Book