Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-RecSys
A curated list of awesome Recommender System (Books, Conferences, Researchers, Papers, Github Repositories, Useful Sites, Youtube Videos)
https://github.com/jihoo-kim/awesome-RecSys
Last synced: about 19 hours ago
JSON representation
-
7. Youtube Videos
- Machine Learning for Recommender Systems
- RecSys Paper Presentation Videos
- Building Recommender System with Machine Learning and AI
- Machine Learning - FULL COURSE | Andrew Ng | Stanford University
- Mining Massive Datasets - FULL COURSE | Stanford University
- Recommendation Systems - Learn Python for Data Science #3
- How does Netflix recommend movies? Matrix Factorization
- Machine Learning for Recommender Systems
- Mining Massive Datasets - FULL COURSE | Stanford University
- Building Recommender System with Machine Learning and AI
- Machine Learning - FULL COURSE | Andrew Ng | Stanford University
-
1. Books
-
2. Conferences
-
3. Researchers
- George Karypis
- Joseph A. Konstan
- Philip S. Yu
- Charu Aggarwal
- Martin Ester
- Paul Resnick
- Peter Brusilovsky
- Bamshad Mobasher
- Alexander Tuzhilin
- Yehuda Koren
- Barry Smyth
- Lior Rokach - Gurion University of the Negev)
- Loren Terveen
- Chris Volinsky
- Ed H. Chi
- Laks V.S. Lakshmanan
- Badrul Sarwar
- Francesco Ricci - Bolzano)
- Robin Burke
- Brent Smith
- Greg Linden
- Hao Ma
- Giovanni Semeraro
- Dietmar Jannach
- Yehuda Koren
- Badrul Sarwar
- Brent Smith
-
4. Papers
- Deep Learning based Recommender System: A Survey and New Perspectives
- Collaborative Variational Autoencoder for Recommender Systems
- Neural Collaborative Filtering
- Deep Neural Networks for YouTube Recommendations
- Wide & Deep Learning for Recommender Systems - Tze Cheng)
- Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
- AutoRec: Autoencoders Meet Collaborative Filtering
- Collaborative Deep Learning for Recommender Systems
- Collaborative Filtering beyond the User-Item Matrix A Survey of the State of the Art and Future Challenges
- Time-aware Point-of-interest Recommendation
- Location-based and Preference-Aware Recommendation Using Sparse Geo-Social Networking Data
- Context-Aware Recommender Systems for Learning: A Survey and Future Challenges
- Exploiting Geographical Influence for Collaborative Point-of-Interest Recommendation
- Recommender Systems with Social Regularization
- The YouTube Video Recommendation System
- Matrix Factorization Techniques for Recommender Systems
- A Survey of Collaborative Filtering Techniques
- Collaborative Filtering with Temporal Dynamics
- Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model
- Collaborative Filtering for Implicit Feedback Datasets
- SoRec: social recommendation using probabilistic matrix factorization
- Flickr tag recommendation based on collective knowledge
- Restricted Boltzmann machines for collaborative filtering
- Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions
- Evaluating collaborative filtering recommender systems
- Amazon.com Recommendations: Item-to-Item Collaborative Filtering
- Content-boosted collaborative filtering for improved recommendations
- Item-based collaborative filtering recommendation algorithms
- Explaining collaborative filtering recommendations
- An algorithmic framework for performing collaborative filtering
- Empirical analysis of predictive algorithms for collaborative filtering
- Social information filtering: Algorithms for automating "word of mouth"
- GroupLens: an open architecture for collaborative filtering of netnews
- Using collaborative filtering to weave an information tapestry
- Explainable Recommendation: A Survey and New Perspectives
- Context-Aware Recommender Systems for Learning: A Survey and Future Challenges
- Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
- A Survey of Collaborative Filtering Techniques
- Wide & Deep Learning for Recommender Systems - Tze Cheng)
-
6. Useful Sites
- WikiCFP - Recommender System - Recommender System)
- PapersWithCode - Recommender System - Recommender System)
- Coursera - Recommender System - Joseph A. Konstan)
- Guide2Research - Top CS Conference
-
8. SlideShare PPT
Categories
Sub Categories