1, towards?
Next generation recommendation system: the latest technology and?
Possible extensions. Overview of the most classical recommendation algorithms
2. Collaborative filtering recommendation system. Overview of JB Schafer's most classic collaborative filtering.
3. Hybrid recommendation system: summary and experiment.
4. Dr. Xiang Liang's thesis "Research on Key Technologies of Dynamic Recommendation System"
5. Research progress of personalized recommendation system. Zhou Tao et al.
6. Recommended systems Lu, Mei Duo, Yang, Zhang, Zhou.
Physical report 5 19 (1), 1-49 (patching system. Y collen
2. Use collaborative filtering to weave information tapestry. David Goldberg (first proposed collaborative filtering)
3. Project-based collaborative filtering recommendation algorithm. Badriel Sawar, George Caripis, Joseph Constance. Extract, transform and load to the destination (abbreviation of extract-transform-load)
4. The application of dimensionality reduction in recommendation system-case study. Mccullough, Robert a.
5. Collaborative filtering based on probabilistic memory. Yu Kai, Anton Yeshaayahu Schwager Hof, Volker Trapp, Xu Xiaowei and Hans-Peter Crighel.
6. Recommendation system: probability analysis. Ravi Kumar Prabhakar Raghavan.etl
7.Amazon.com recommended: collaborative filtering from project to project. Greg Linden, Brent Smith and Jeremy York
8. Evaluation of Top- N recommendation algorithm based on project. George caripis
9. Probability matrix decomposition. Ruslan Sarahutinov
10. Tensor decomposition, alternating least squares and other stories. Pierre Comon, Javier Luciani, Andre de Almeida
Content-based recommendation:?
1. Content-based recommendation system. Michael pazzani and Daniel Bilsus.
Tag-based recommendation:?
1. Tag-aware recommendation system: a new survey. Zi (Zhang Zikai), (Zhou Tao), and (Zhang Yicheng).
Recommended evaluation index:?
1, summary of recommended system evaluation indicators. Zhu, Lu
2. Accuracy is not always good: How does the accuracy index hurt the recommendation system?
3. Evaluate the recommendation system. Guy Nisha and acera Gonnewardene
4. Evaluate collaborative filtering recommendation system. JL Helok
Recommend diversity and novelty:
1. Improve the recommendation list through topic diversification. Cai-Nikolai Ziegler
Sean McNee, Joseph Constance, Georg Lawson
Recommender System Based on Fusion to Improve Adventure Degree
Maximizing Diversity of Set Recommendation: A Graph Theory Approach
Forgetting problem: improving recommendation diversity by using forgetting items
Framework for recommending collections
Improve the diversity of recommendations. Keith Bradley and Barry Smith
Privacy protection in recommendation system:?
1, collaborative filtering with privacy. John Canny
2. Do you believe your recommendation? Discussion on security and privacy in recommendation system. Yang K "Tony" Lin, Dan Frankowski, John Reid.
3. Personalization of privacy enhancement. Alfred Kobsa
4. Differentiated private recommendation system: integrating privacy?
Netflix award contender. Frank McSherry and Ilya mironov Microsoft Research Institute?
Silicon valley campus
5. When the weak are brave: privacy issues in the recommendation system. Na Ren Ramakrishnan, Benjamin Keller and Batoul Mi Erzha.
Recommended cold start question:?
1. Cold start the recommended bound Boltzmann machine. Acera Gonnewardene
2. Paired preference regression for cold start recommendation. Weichu Chengze Park
3. Solve the cold start problem in the recommendation system. Xuanyilin. etl
4. Suggested methods and indicators for cold start. Mccullough, Robert J.
Bandit (slot machine algorithm, which can alleviate the cold start problem):
1, bandits and recommendation system. Jeremy Marie, Roman Rick Godell, Philip Puller
2. Multi-arm Bandit algorithm and empirical evaluation.
Recommendations based on social networks:?
1. Social recommendation system. Ido Gay and David Carmel
A recommendation system (SNRS) based on social network. He Jianming and Zhu Weili
Measurement and analysis of online social network.
Recommended websites: combining social networks and collaborative filtering
Knowledge recommendation:?
1, knowledge recommendation system. Robin Burke
2. Case-based recommendation. Barry Smith
3. Constraint-based recommendation system: technology and research issues. Fairverning Burke
Others:?
Trust-aware recommendation system. Paulo Mazza and Paul Afsani