Can you recommend a book with good information that can be applied to developing a recommender system?
An 800+ page definitive guide from the top experts in the field (pricey though): Recommender Systems Handbook. Each chapter is written by different folks (one could try googling specific chapters - some of them are freely available on the web)
For a very basic introduction you could check out chapter 2 of Programming Collective Intelligence.
An introductory book would be this one here. He describes several algorithms for recommender systems in a simple addition to having several references if you'd like to know more about a technique especifismo. Besides this, here is this other kind of a collection of articles.
It's not a book and it's not organized, but it contains many algorithms, links, code and paper references: http://www.netflixprize.com/community/forum.html . You may download all the data as tarball.
I wrote a monograph about the Netflix Prize and recommender systems: "Predicting movie ratings and recommender systems"
Here are some of the books and Research Publications on Recommendation Systems
Free & downloadable (Good introduction on Collaborative Filtering Recommendation) http://md.ekstrandom.net/research/pubs/cf-survey/
Other books are -
Recommender Systems - Introduction
Recommender Systems - Handbook
The books mentioned here are amazing in-depth that catch you up to most recent research in the field. I wrote a chapter in Data Mining Applications with R that gets you up and running to the point of writing and testing your own recommendation algorithms quickly. This is not as in depth as the other books and is only a starter template. You will still need to read these books and papers in the field to learn more about the topic.