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Collective Intelligence in Action 1st Edition
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About the Author
Satnam Alag, PhD, is currently the Vice President of Engineering at NextBio, a vertical search engine and a Web 2.0 collaboration application for the life sciences community. He is a seasoned software professional with over fifteen years of experience in machine learning and over a decade of experience in commercial software development and management. Dr. Alag worked as a consultant with Johnson & Johnsons's BabyCenter where he helped develop their personalization engine. Prior to that, he was the Chief Software Architect at Rearden Commerce and began his career at GE R&D. He is a Sun Certified Enterprise Architect (SCEA) for the Java Platform. Dr. Alag earned his PhD in engineering from UC Berkeley and his dissertation was in the area of probabilistic reasoning and machine learning. He has published numerous peer-reviewed articles.
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Top Customer Reviews
The first chapter is free and so is the source code used in the book.
The book is for Java developers who want to implement "Collective Intelligence" applications in Java. It tells us about extracting and applying data from blogs, wikis and social network applications. I am not one to praise, but this book succeeds brilliantly. If you are a Java engineer and work with Web technologies, you must get this book. It covers topics such as computing similarity measures using vector models, Nai've Bayes Classifiers, inverse document frequency (idf), Machine Learning (using the Weka API), building a crawler with regular expressions, collaborative filtering (with links to open source tools), and so on.
Even if you do not work with Java, if you care for high-end Web applications, this book is for you. It reminds me of Lyon's Java¿ Digital Signal Processing book. It offers the gist of what academia knows, but focuses on what people (engineers and researchers) do in practise.
The book is not meant for academia however. There are references, but no theorem.
Disclaimer. I did not get paid to review this book, and I do not stand to gain anything if you buy the book. I have no relationship with the publisher or the author.
Further reading. A competing book is Programming Collective Intelligence: Building Smart Web 2.0 Applications by Toby Segaran. It uses Python instead of Java.
when I logged into the Amazon.com site. Yes, this kind of functionality is very easy to
implement into your application after reading Satnam's Collective Intelligence in Action
Have you ever wonder how Netflix is able to recommend movies, what are the latest trends
in the making search more intelligent or how you can intelligently gather new content and
present it to your application?
In this book, Santnam does an excellent job providing the answers to all these questions
The book covers the wide breadth of the topics with amazing focus and detail-architecture
for adding intelligence, tagging and tag clouds, content aggregation through focused web
crawling and from the blogospare, leveraging machine learning techniques such as clustering
and predictive modeling, intelligent search and building recommendation engine.
I particularly liked the approach to explain the mathematical concepts with simple examples,
followed by implementing it in simple Java and then leveraging open-source software.
This book can be very useful if you are interested in integrating different Open Source Softwares
to deliver Enterprise Class Application.
I also liked the authors style of providing summary at the end of each chapter.
He also provides huge set of very useful resources for reading further on the topics
covered into the chapters.
You must pickup this book if you are
.Read more ›
The basic idea is that one can catalog documents by removing irrelevant words (adjectives, abstract pronouns, conjunctives) and "stemming" the remaining words (ie: reducing "sews", "sewing", "resew", "sewer" to a root "sew") and creating a vector containing each root word and the word frequency and then normalizing it. One simple result is the ability to produce "word clouds". Similarity between documents is measured by taking the dot product of the two vectors. Any document compared to itself would have a dot product of 1. Two documents with no common stem words would have a dot product of zero. Similar docs would have a high value close to 1, say .8. Dissimilar docs would have a low coefficient, say .15. Even mistaking "sewer" (a conduit for waste) and sewer (one who uses a needle and thread) is taken into account because both docs would only be similar on a couple of keywords, and dissimilar on most others.
What's really neat is how this information gets collected and can be applied. Social networking sites, including the one you are reading right now, Amazon.com, collect data on us through our choices. Browse for a book while logged on then that's something you are interested in. Approve a review the words in the review, summary of the book and the title counts towards your interests. Disapprove and that counts against your interests.Read more ›
Most Recent Customer Reviews
This book is a great introduction to CI for people who are starting out. The coverage is broad rather than deep - along with the expected theoretical background on Term-Document... Read morePublished on October 18, 2010 by Sujit Pal
This book contains a lot of ideas and as such is a good starting point for further reading. But it's not a one-stop resource for actually implementing the algorithms it mentions,... Read morePublished on July 19, 2010 by G. Webster
I'm a start-up CEO, who's had 3 of my engineers review this book. Unanimously, they came back raving about how much they picked up from the book and hence how much time they saved. Read morePublished on May 19, 2010 by Ankesh Kumar
This book is more deserving of the "Collective Intelligence" title than O'Reilly's "Programming Collective Intelligence" as it's not just about algorithms, but discusses blogs,... Read morePublished on November 11, 2009 by Eric Jain
The best thing about the book is that it revealed many other open source toolkits relevant to the topic. Provided good topic background. Read morePublished on October 8, 2009 by Vasko Yordanov
Collective Intelligence is a big topic so the title of this book is very ambitious. The author is too. He sets out to explain all things collective intelligence circa 2009. Read morePublished on June 4, 2009 by Glenn
The publisher has fixed the most errata listed on O'reilly website in the edition I got from Amazon. Read morePublished on April 10, 2009 by Jun Zhang
In my opinion, this book is intended for people with good knowledge in Business Intelligence as well as Java to understand the examples provided, but this is a practical book for... Read morePublished on March 16, 2009 by Developpez.com writers