Ensemble Methods in Data Mining: Improving Accuracy Through Combining Prediction is a book that I definitively recommends if are interested in latest data mining trends.
A couple of years ago, I got fascinated by the simplicity of Adaboost algorithm and the amazing performance it offers for mining quite different sets of data. Adaboost is based on a very simple intuition: you start with a very simple and naive classifiers and then you improve the performance with boosting techniques. After that, I started to read papers about RandomForest, Bagging, Mart and many other boosting methodologies but I felt the lack of an unifying approach and description of all those techniques.
Ensemble Methods in Data Mining: Improving Accuracy Through Combining Prediction offers this view by giving a description of the ISLE framework in a very synthetic yet detailed exposition. Great work!