I hesitated when I started reading the chapter describing search and how to build a search engine, I felt it was included just as filler for the book (a few chapters to add 100 pages or so). And I figured their are already too many books on how to build search engines. I am glad I pushed through, for once I started reading I began to see the point of describing and building a search engine. Descriptions (with source code) of how collective intelligence algorithms can be integrated into search were introduced. This is a huge and important topic when you think about social search and the use of the social graph is contributing and impact collective intelligence could have on search.
As I got into the later chapters I began to realize just how comprehensive the coverage of programming collective intelligence the book provides. I was particularly interested in the support vector machine and genetic programming. Even, though I do not commonly find myself programming in any depth I found the descriptions of these rather heady subjects well described and easy to understand. I also appreciated the closing chapters of the book where a review of the different algorithms is provided, how they are best utilized and their strengths and weaknesses. References to all the third party libraries was put into a single appendix as were all the mathematical formula.
Going through this book cover to cover, reading the examples and diving into a few (or all) of the exercises gives the reader a very good understanding of how much data and intelligent services are already available via API's on the Internet. Programming against these services and creating new services is a big part of the Internet as a research, knowledge and learning environment. Anyone interested in developing these new services, consuming these existing ones or interested in the mathematics behind collective intelligence, I strongly recommend this book.
