Recommender Systems with Deep Learning

This blog post presents recent research in Recommender Systems (/collaborative filtering) with Deep Learning. To get started I recommend having a look at A Survey and Critique of Deep Learning in Recommender Systems.

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Best regards,
Amund Tveit


Recommender Systems with Deep Learning

  1. Improving Scalability of Personalized Recommendation Systems for Enterprise Knowledge Workers
    – Authors: C Verma, M Hart, S Bhatkar, A Parker (2016)
  2. Multi-modal learning for video recommendation based on mobile application usage
    – Authors: X Jia, A Wang, X Li, G Xun, W Xu, A Zhang (2016)
  3. Collaborative Filtering with Stacked Denoising AutoEncoders and Sparse Inputs
    – Authors: F Strub, J Mary (2016)
  4. Applying Visual User Interest Profiles for Recommendation and Personalisation
    – Authors: J Zhou, R Albatal, C Gurrin (2016)
  5. Comparative Deep Learning of Hybrid Representations for Image Recommendations
    – Authors: C Lei, D Liu, W Li, Zj Zha, H Li (2016)
  6. Tag-Aware Recommender Systems Based on Deep Neural Networks
    – Authors: Y Zuo, J Zeng, M Gong, L Jiao (2016)
  7. Quote Recommendation in Dialogue using Deep Neural Network
    – Authors: H Lee, Y Ahn, H Lee, S Ha, S Lee (2016)
  8. Toward Fashion-Brand Recommendation Systems Using Deep-Learning: Preliminary Analysis
    – Authors: Y Wakita, K Oku, K Kawagoe (2016)
  9. Word embedding based retrieval model for similar cases recommendation
    – Authors: Y Zhao, J Wang, F Wang (2016)
  10. ConTagNet: Exploiting User Context for Image Tag Recommendation
    – Authors: Ys Rawat, Ms Kankanhalli (2016)
  11. Wide & Deep Learning for Recommender Systems
    РAuthors: Ht Cheng, L Koc, J Harmsen, T Shaked, T Chandra… (2016)
  12. On Deep Learning for Trust-Aware Recommendations in Social Networks.
    – Authors: S Deng, L Huang, G Xu, X Wu, Z Wu (2016)
  13. A Survey and Critique of Deep Learning on Recommender Systems
    – Authors: L Zheng (2016)
  14. Collaborative Filtering and Deep Learning Based Hybrid Recommendation for Cold Start Problem
    – Authors: J Wei, J He, K Chen, Y Zhou, Z Tang (2016)
  15. Collaborative Filtering and Deep Learning Based Recommendation System For Cold Start Items
    – Authors: J Wei, J He, K Chen, Y Zhou, Z Tang (2016)
  16. Deep Neural Networks for YouTube Recommendations
    – Authors: P Covington, J Adams, E Sargin (2016)
  17. Towards Latent Context-Aware Recommendation Systems
    – Authors: M Unger, A Bar, B Shapira, L Rokach (2016)
  18. Automatic Recommendation Technology for Learning Resources with Convolutional Neural Network
    – Authors: X Shen, B Yi, Z Zhang, J Shu, H Liu (2016)
  19. Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling
    – Authors: Z Xu, C Chen, T Lukasiewicz, Y Miao, X Meng (2016)
  20. Latent Factor Representations for Cold-Start Video Recommendation
    – Authors: S Roy, Sc Guntuku (2016)
  21. Convolutional Matrix Factorization for Document Context-Aware Recommendation
    – Authors: D Kim, C Park, J Oh, S Lee, H Yu (2016)
  22. Conversational Recommendation System with Unsupervised Learning
    – Authors: Y Sun, Y Zhang, Y Chen, R Jin (2016)
  23. RecSys’ 16 Workshop on Deep Learning for Recommender Systems (DLRS)
    – Authors: A Karatzoglou, B Hidasi, D Tikk, O Sar (2016, Workshop proceedings)
  24. Ask the GRU: Multi-task Learning for Deep Text Recommendations
    – Authors: T Bansal, D Belanger, A Mccallum (2016)
  25. Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation
    – Authors: H Dai, Y Wang, R Trivedi, L Song (2016)
  26. Keynote: Deep learning for audio-based music recommendation
    – Authors: S Dieleman (2016)
  27. Tumblr Blog Recommendation with Boosted Inductive Matrix Completion
    – Authors: D Shin, S Cetintas, Kc Lee, Is Dhillon (2015)
  28. Deep Collaborative Filtering via Marginalized Denoising Auto-encoder
    – Authors: S Li, J Kawale, Y Fu (2015)
  29. Learning Image and User Features for Recommendation in Social Networks
    – Authors: X Geng, H Zhang, J Bian, Ts Chua (2015)
  30. UCT-Enhanced Deep Convolutional Neural Network for Move Recommendation in Go
    – Authors: S Paisarnsrisomsuk (2015)
  31. A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems
    – Authors: A Elkahky, Y Song, X He (2015)
  32. It Takes Two to Tango: An Exploration of Domain Pairs for Cross-Domain Collaborative Filtering
    – Authors: S Sahebi, P Brusilovsky (2015)
  33. Latent Context-Aware Recommender Systems
    – Authors: M Unger (2015)
  34. Learning Distributed Representations from Reviews for Collaborative Filtering
    – Authors: A Almahairi, K Kastner, K Cho, A Courville (2015)
  35. A Collaborative Filtering Approach to Real-Time Hand Pose Estimation
    – Authors: C Choi, A Sinha, Jh Choi, S Jang, K Ramani (2015)
  36. Collaborative Deep Learning for Recommender Systems
    – Authors: H Wang, N Wang, Dy Yeung (2014)
  37. CARS2: Learning Context-aware Representations for Context-aware Recommendations
    – Authors: Y Shi, A Karatzoglou, L Baltrunas, M Larson, A Hanjalic (2014)
  38. Relational Stacked Denoising Autoencoder for Tag Recommendation
    – Authors: H Wang, X Shi, Dy Yeung (2014)

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