Most helpful critical review
12 of 14 people found the following review helpful
A lot of ideas, but neither theoretical enough nor pratical enough
on July 19, 2010
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, as a lot of them are described only in a very high level and incomplete way. For example, in the discussion of model-based recommendation engines in sections 12.3.3-12.3.5, the author gives a very short description of latent semantic indexing (LSI) and some Java code that shows how to use the Weka implementation. But firstly, the description is too short to give the user a real understanding of what is going on theoretically. And secondly, the implementation description doesn't go nearly far enough: it shows that reconstructing the original matrix from the top N dimensions of the singular value decomposition gives a close approximation to the original, but then it just stops there; it doesn't explain how to actually use the decomposition in a recommendation engine. And the section on LSI is verbose compared to the "section" on Bayesian belief networks, which at a single paragraph of text is completely inadequate for either practical or theoretical purposes. And so on throughout the book.