Referral System-from beginner to proficient (paper selection)

In order to facilitate everyone from theory to practice, from beginner to proficient, the system of gradual and systematic understanding and mastering the relevant knowledge of recommendation system. He made a reading list. You can read this form, and also welcome suggestions and notes of the non-marked classics to enrich the needs of the various disciplines (to avoid beginners, each direction only recommended a few classic documents).
1. Chinese Overview (Understanding Concepts-Introductory article)
A) research progress of personalized recommendation system OK
b) Summary of evaluation methods for personalized recommendation system OK
2. Summary of English (understanding concept-Advanced article)
A) 2004acmtois-evaluating Collaborative filtering recommender systems OK
b) 2004acmtois-introduction to recommender systems-algorithms and evaluation
c) 2005IEEEtkde toward the next generation of Recommender Systems-a survey of the State-of-the-art and possible Extensio NS OK
3. Hands-on capability (practice algorithm-introductory article)
A) 2004ACMtois item-based top-n recommendation Algorithms (Collaborative filtering) OK
b) 2007PRE bipartite network projection and personal recommendation (Networking structure) OK
4. Hands-on capability (practice algorithm-Advanced)
A) 2010pnas-solving the apparent diversity-accuracy dilemma of recommender systems (material diffusion and heat conduction) OK
b) 2009NJP accurate and diverse recommendations via eliminating redundant correlations (multi-step material diffusion) OK
c) 2008EPL Effect of Initial configuration on network-based recommendation (initial resource allocation problem) NO
5. Recommended system extension Application (Advanced article)
A) 2009EPJB predicting missing links via local information (method of similarity measurement)
b) 2010theis-evaluating Collaborative Filtering over time (PhD dissertation based on temporal effects)
c) 2009PA personalized recommendation via integrated diffusion on User-item-tag tripartite graphs (three-part graphic method based on the label) OK
d) 2004LNCS Trust-aware Collaborative filtering for Recommender systems (based on trust mechanism) OK
e) 1997ca-fab_content-based, collaborative recommendation (text-based information)
6. Explanation of recommended results (Advanced article)
A) 2000cscw-explaining collaborative Filtering recommendations OK
b) 2011pre-information filtering via biased heat conduction
c) 2011pre-information filtering via preferential diffusion OK
d) 2010EPL Link prediction in weighted networks-the role of weak ties OK
e) 2010epl-solving The Cold-start problem in recommender systems with social tags OK
7. Recommendation System synthesis (monographs, large-scale review, doctoral dissertation)
A) 2005ziegler-thesis-towards decentralized recommender Systems OK

b) 2010Recommender Systems Handbook

Referral System-from beginner to proficient (paper selection)