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13th RecSys 2019: Copenhagen, Denmark - Late-Breaking Results
- Marko Tkalcic, Sole Pera:
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. CEUR Workshop Proceedings 2431, CEUR-WS.org 2019 - Dimitris Sacharidis
, Kyriakos Mouratidis, Dimitrios Kleftogiannis:
A Common Approach for Consumer and Provider Fairness in Recommendations. 1-5 - 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? 6-10 - Sarai Mizrachi, Pavel Levin:
Combining Context Features in Sequence-Aware Recommender Systems. 11-15 - Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima:
Context-Regularized Neural Collaborative Filtering for Game App Recommendation. 16-20 - Manel Slokom, Martha A. Larson, Alan Hanjalic:
Data Masking for Recommender Systems: Prediction Performance and Rating Hiding. 21-25 - Jöran Beel, Victor Brunel:
Data Pruning in Recommender Systems Research: Best-Practice or Malpractice? 26-30 - Linus W. Dietz, Wolfgang Wörndl:
How Long to Stay Where? On the Amount of Item Consumption in Travel Recommendation. 31-35 - Pan Li, Alexander Tuzhilin:
Latent Modeling of Unexpectedness for Recommendations. 36-40 - Sheng-Chieh Lin, Yu-Neng Chuang, Sheng-Fang Yang, Ming-Feng Tsai, Chuan-Ju Wang:
Negative-Aware Collaborative Filtering. 41-45 - Jan Van Balen, Mark Levy:
PQ-VAE: Efficient Recommendation Using Quantized Embeddings. 46-50 - Wanling Cai, Li Chen:
Towards a Taxonomy of User Feedback Intents for Conversational Recommendations. 51-55 - 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. 56-60 - Maria Soledad Pera, Emiliana Murgia, Monica Landoni, Theo Huibers:
With a Little Help from my Friends: Use of Recommendations at School. 61-65
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