Outlier Analysis by Charu Aggarwal (Springer, January 2013). Post by Gregory Piatetsky.
From the post:
This is an authored text book on outlier analysis. The book can be considered a first comprehensive text book in this area from a data mining and computer science perspective. Most of the earlier books in outlier detection were written from a statistical perspective, and precede the emergence of the data mining field over the last 15-20 years.
Each chapter contains carefully organized content on the topic, case studies, extensive bibliographic notes and the future direction of research in this field. Thus, the book can also be used as a reference aid. Emphasis was placed on simplifying the content, so that the material is relatively easy to assimilate. The book assumes relatively little prior background, other than a very basic understanding of probability and statistical concepts. Therefore, in spite of its deep coverage, it can also provide a good introduction to the beginner. The book includes exercises as well, so that it can be used as a teaching aid.
Table of Contents and Introduction. Includes exercises and a 500+ reference bibliography.
Definitely a volume for the short reading list.
Caveat: As an outlier by any measure, my opinions here may be biased. 😉