Subjects:

1. Recommender System
2. Collaborative Filtering
3. Long Tail

Groups & Researchers:

1. GroupLens Lab
2. Karypis Lab
3. Thomas Hofmann
4. David M. Pennock

Conferences:

1. RecSys 2007
2. KDD Cup and Workshop 2007

Selected Papers:

1. Paul Resnick, GroupLens — An Open Architecture for Collaborative Filtering of Netnews
2. Badrul Sarwar, Item-based Collaborative Filtering Recommendation Algorithms
3. Greg Linden, Amazon.com Recommendations: Item-to-Item Collaborative Filtering
4. Thomas Hofmann, Latent Semantic Models for Collaborative Filtering
5. 4 googlers, Google News Personalization – Scalable Online Collaborative Filtering

Blogers:

1. Greg Linden
2. Daniel Lemire
3. Duke Listens!

Software Libraries:

1. Taste, Java, http://taste.sf.net/
2. Beyond Thoth, C#, http://sf.net/projects/beyondthoth/

Resources:

1. Stanford CS345: Data Mining
2. http://del.icio.us/tag/collaborativefiltering
3. http://del.icio.us/tag/recommendersystem

Books:
完全以个性化技术为中心的书籍很少，但多数讲 Machine Learning 或者 Data Mining 的书籍里面，都会有专门的章节，介绍与此相关的内容。

1. Programming Collective Intelligence, Toby Segaran, O'Reilly, 2007.8
2. Personalization Techniques and Recommender Systems, Gulden Uchyigit, World Scientific, 2008.4