A short review of Collective Intelligence in Action

I was recently asked by the publisher to review Collective Intelligence in Action. The author is Satnam Alag, a Bay area engineer with a Ph.D. from the University of California, Berkeley. Dr. Alag is VP of NextBio, a specialized search engine.

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. People who read this blog know that 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, Naïve 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 practice.

The book is not meant for academia however. There are references, but no theorem.

The book is available for preorder on Amazon for $30. Go order it.

Disclosure. 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.

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