The book covers a number of topics that come up frequently in data mining: reworking algorithms into a map-reduce paradigm, finding similar items, mining streams of data, finding frequent items, clustering, and recommending items. Unlike many texts on the subject, you won’t find source-code in this book; but rather, extensive explanations of multiple techniques and algorithms to address each topic. This lends itself to a better understanding of the theory, so that you understand the trade-offs you might be making when implementing your own systems.

There are easier texts to get through, but if you’re getting started with recommendation or data-mining systems, and haven’t read this book, I’d encourage you to do so.