RecSys (Late-Breaking Results)

Keyphrases

Publications

2019

Kyung-Min Kim, Dong-Hyun Kwak, Hanock Kwak, Young-Jin Park, Sangkwon Sim, Jae-Han Cho, Minkyu Kim, Jihun Kwon, Nako Sung, Jung-Woo Ha
Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation. RecSys (Late-Breaking Results) (2019)
Sarai Mizrachi, Pavel Levin
Combining Context Features in Sequence-Aware Recommender Systems. RecSys (Late-Breaking Results) (2019)
Wanling Cai, Li Chen
Towards a Taxonomy of User Feedback Intents for Conversational Recommendations. RecSys (Late-Breaking Results) (2019)
Sheng-Chieh Lin, Yu-Neng Chuang, Sheng-Fang Yang, Ming-Feng Tsai, Chuan-Ju Wang
Negative-Aware Collaborative Filtering. RecSys (Late-Breaking Results) (2019)
Jöran Beel, Victor Brunel
Data Pruning in Recommender Systems Research: Best-Practice or Malpractice? RecSys (Late-Breaking Results) (2019)
Hebatallah A. Mohamed Hassan, Giuseppe Sansonetti, Fabio Gasparetti, Alessandro Micarelli, Jöran Beel
BERT, ELMo, USE and InferSent Sentence Encoders: The Panacea for Research-Paper Recommendation? RecSys (Late-Breaking Results) (2019)
Manel Slokom, Martha A. Larson, Alan Hanjalic
Data Masking for Recommender Systems: Prediction Performance and Rating Hiding. RecSys (Late-Breaking Results) (2019)
Jan Van Balen, Mark Levy
PQ-VAE: Efficient Recommendation Using Quantized Embeddings. RecSys (Late-Breaking Results) (2019)
Pan Li, Alexander Tuzhilin
Latent Modeling of Unexpectedness for Recommendations. RecSys (Late-Breaking Results) (2019)
Dimitris Sacharidis, Kyriakos Mouratidis, Dimitrios Kleftogiannis
A Common Approach for Consumer and Provider Fairness in Recommendations. RecSys (Late-Breaking Results) (2019)
Linus W. Dietz, Wolfgang Wörndl
How Long to Stay Where? On the Amount of Item Consumption in Travel Recommendation. RecSys (Late-Breaking Results) (2019)
Maria Soledad Pera, Emiliana Murgia, Monica Landoni, Theo Huibers
With a Little Help from my Friends: Use of Recommendations at School. RecSys (Late-Breaking Results) (2019)
Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima
Context-Regularized Neural Collaborative Filtering for Game App Recommendation. RecSys (Late-Breaking Results) (2019)

volume 2431, 2019

Proceedings of ACM RecSys 2019 Late-Breaking Results co-located with the 13th ACM Conference on Recommender Systems, RecSys 2019 Late-Breaking Results, Copenhagen, Denmark, September 16-20, 2019. RecSys (Late-Breaking Results) 2431 (2019)