Recommender Systems with Deep Learning
Alessandro:ADA
Alessandro Suglia, Claudio Greco, Cataldo Musto, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro:
A Deep Architecture for Content-based Recommendations Exploiting Recurrent Neural Networks. UMAP 2017: 202-211
Haochao：CDR
Haochao Ying, Liang Chen, Yuwen Xiong, Jian Wu:
Collaborative Deep Ranking: A Hybrid Pair-Wise Recommendation Algorithm with Implicit Feedback. PAKDD (2) 2016: 555-567
Paul:DNN
Paul Covington, Jay Adams, Emre Sargin:
Deep Neural Networks for YouTube Recommendations. RecSys 2016: 191-198
Ali：AMV
Ali Mamdouh Elkahky, Yang Song, Xiaodong He:
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems. WWW 2015: 278-288
Jian：CFD
Jian Wei, Jianhua He, Kai Chen, Yi Zhou, Zuoyin Tang:
Collaborative filtering and deep learning based recommendation system for cold start items. Expert Syst. Appl. 69: 29-39 (2017)
Xin：AHC
Xin Dong, Lei Yu, Zhonghuo Wu, Yuxia Sun, Lingfeng Yuan, Fangxi Zhang:
A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems. AAAI 2017: 1309-1315
Improving Scalability of Personalized Recommendation Systems for Enterprise Knowledge Workers
– Authors: C Verma, M Hart, S Bhatkar, A Parker (2016)
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)
Collaborative Filtering with Stacked Denoising AutoEncoders and Sparse Inputs
– Authors: F Strub, J Mary (2016)
Applying Visual User Interest Profiles for Recommendation and Personalisation
– Authors: J Zhou, R Albatal, C Gurrin (2016)
Comparative Deep Learning of Hybrid Representations for Image Recommendations
– Authors: C Lei, D Liu, W Li, Zj Zha, H Li (2016)
Tag-Aware Recommender Systems Based on Deep Neural Networks
– Authors: Y Zuo, J Zeng, M Gong, L Jiao (2016)
Quote Recommendation in Dialogue using Deep Neural Network
– Authors: H Lee, Y Ahn, H Lee, S Ha, S Lee (2016)
Toward Fashion-Brand Recommendation Systems Using Deep-Learning: Preliminary Analysis
– Authors: Y Wakita, K Oku, K Kawagoe (2016)
Word embedding based retrieval model for similar cases recommendation
– Authors: Y Zhao, J Wang, F Wang (2016)
ConTagNet: Exploiting User Context for Image Tag Recommendation
– Authors: Ys Rawat, Ms Kankanhalli (2016)
Wide & Deep Learning for Recommender Systems
– Authors: Ht Cheng, L Koc, J Harmsen, T Shaked, T Chandra… (2016)
On Deep Learning for Trust-Aware Recommendations in Social Networks.
– Authors: S Deng, L Huang, G Xu, X Wu, Z Wu (2016)
A Survey and Critique of Deep Learning on Recommender Systems
– Authors: L Zheng (2016)
Collaborative Filtering and Deep Learning Based Hybrid Recommendation for Cold Start Problem
– Authors: J Wei, J He, K Chen, Y Zhou, Z Tang (2016)
Collaborative Filtering and Deep Learning Based Recommendation System For Cold Start Items
– Authors: J Wei, J He, K Chen, Y Zhou, Z Tang (2016)
Deep Neural Networks for YouTube Recommendations
– Authors: P Covington, J Adams, E Sargin (2016)
Towards Latent Context-Aware Recommendation Systems
– Authors: M Unger, A Bar, B Shapira, L Rokach (2016)
Automatic Recommendation Technology for Learning Resources with Convolutional Neural Network
– Authors: X Shen, B Yi, Z Zhang, J Shu, H Liu (2016)
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)
Latent Factor Representations for Cold-Start Video Recommendation
– Authors: S Roy, Sc Guntuku (2016)
Convolutional Matrix Factorization for Document Context-Aware Recommendation
– Authors: D Kim, C Park, J Oh, S Lee, H Yu (2016)
Conversational Recommendation System with Unsupervised Learning
– Authors: Y Sun, Y Zhang, Y Chen, R Jin (2016)
RecSys’ 16 Workshop on Deep Learning for Recommender Systems (DLRS)
– Authors: A Karatzoglou, B Hidasi, D Tikk, O Sar (2016, Workshop proceedings)
Ask the GRU: Multi-task Learning for Deep Text Recommendations
– Authors: T Bansal, D Belanger, A Mccallum (2016)
Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation
– Authors: H Dai, Y Wang, R Trivedi, L Song (2016)
Keynote: Deep learning for audio-based music recommendation
– Authors: S Dieleman (2016)
Tumblr Blog Recommendation with Boosted Inductive Matrix Completion
– Authors: D Shin, S Cetintas, Kc Lee, Is Dhillon (2015)
Deep Collaborative Filtering via Marginalized Denoising Auto-encoder
– Authors: S Li, J Kawale, Y Fu (2015)
Learning Image and User Features for Recommendation in Social Networks
– Authors: X Geng, H Zhang, J Bian, Ts Chua (2015)
UCT-Enhanced Deep Convolutional Neural Network for Move Recommendation in Go
– Authors: S Paisarnsrisomsuk (2015)
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems
– Authors: A Elkahky, Y Song, X He (2015)
It Takes Two to Tango: An Exploration of Domain Pairs for Cross-Domain Collaborative Filtering
– Authors: S Sahebi, P Brusilovsky (2015)
Latent Context-Aware Recommender Systems
– Authors: M Unger (2015)
Learning Distributed Representations from Reviews for Collaborative Filtering
– Authors: A Almahairi, K Kastner, K Cho, A Courville (2015)
A Collaborative Filtering Approach to Real-Time Hand Pose Estimation
– Authors: C Choi, A Sinha, Jh Choi, S Jang, K Ramani (2015)
Collaborative Deep Learning for Recommender Systems
– Authors: H Wang, N Wang, Dy Yeung (2014)
CARS2: Learning Context-aware Representations for Context-aware Recommendations
– Authors: Y Shi, A Karatzoglou, L Baltrunas, M Larson, A Hanjalic (2014)
Relational Stacked Denoising Autoencoder for Tag Recommendation
– Authors: H Wang, X Shi, Dy Yeung (2014)