Collective Intelligence in Action Review

Average Reviews:

(More customer reviews)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. 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.

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There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob.

In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users.

Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches.

This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit.

Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard.

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