WWW

官网: www2016 accepted papers


AAAI


SIGIR

官网: sigir2016 accepted papers


VLDB

vldb2016 accepted papers


Recsys

官网: recsys2016 accepted papers

豆瓣recsys2016总结

1. A Scalable Approach for Periodical Personalized Recommendations
2. Adaptive, Personalized Diversity for Visual Discovery
3. Field-aware Factorization Machines for CTR Prediction
4. Local Item-Item Models for Top-N Recommendation (Best paper)
5. Mechanism Design for Personalized Recommender Systems
6. Deep Neural Networks for YouTube Recommendations
7. Past, Present, and Future of Recommender Systems: An Industry Perspective (author:Xavier Amatriain)
8. Algorithms Aside: Recommendation as the Lens Of Life (演讲的胶片非常艺术流)
9. Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation
10. Are You Influenced by Others When Rating? Improve Rating Prediction by Conformity Modeling (余勇老师组做的工作)
11. Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Task
工业界的几篇论文:
1. When Recommendation Systems Go Bad (meetup)
2. News Recommendations at scale at Bloomberg Media: Challenges and Approaches (Bloomber)
3. Marsbot: Building a Personal Assistant (Foursqure)
4. Music Personalization at Spotify (Spotify)
5. Recommending for the World (Netflix)
6. The Exploit-Explore Dilemma in Music Recommendation (Pandora)
7. Tutorial: Lessons Learned from Building Real-life Recommender Systems (Xavier’ tutorial)

KDD

官网: kdd2016 accepted papers

  1. Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applic
  2. Point-of-Interest Recommendations: Learning Potential Check-ins from Friends
  3. The Limits of Popularity-Based Recommendations, and the Role of Social Ties
  4. Unified Point-of-Interest Recommendation with Temporal Interval Assessment
  5. Towards Conversational Recommender Systems
  6. Online Context-Aware Recommendation with Time Varying Multi-Arm Bandit
  7. Data-driven Automatic Treatment Regimen Development and Recommendation
  8. The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation
  9. An Empirical Study on Recommendation with Multiple Types of Feedback
  10. Collaborative Knowledge Base Embedding for Recommender Systems

IJCAI

ijcai2016 accept papers


CIKM

cikm2016 accepted papers


ICDM

icdm 2016 accepted papers


ICDE

icde2016 accepted papers


 



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neiniu 2017-03-12 11:56:18

俞勇,不是余勇


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