Dynamic Embeddings for Interaction Prediction-Reference-Cited by-同舟云学术

Dynamic Embeddings for Interaction Prediction

Published:2021-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Web Conference 2021
language:
Short-container-title:

Author:

Kefato Zekarias¹,Girdzijauskas Sarunas¹,Sheikh Nasrullah²,Montresor Alberto³

Affiliation:

1. KTH Royal Institute of Technology, Sweden

2. IBM, USA

3. University of Trento, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3442381.3450020

Reference37 articles.

1. M. Belkin and P. Niyogi. 2003. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. M. Belkin and P. Niyogi. 2003. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.

2. Latent Cross

3. Krisztian Buza and Ladislav Peška. 2017. Drug–target interaction prediction with Bipartite Local Models and hubness-aware regression. Krisztian Buza and Ladislav Peška. 2017. Drug–target interaction prediction with Bipartite Local Models and hubness-aware regression.

4. Deep Neural Networks for YouTube Recommendations

5. Hanjun Dai Yichen Wang Rakshit Trivedi and Le Song. 2016. Deep Coevolutionary Network: Embedding User and Item Features for Recommendation. arxiv:1609.03675 [cs.LG] Hanjun Dai Yichen Wang Rakshit Trivedi and Le Song. 2016. Deep Coevolutionary Network: Embedding User and Item Features for Recommendation. arxiv:1609.03675 [cs.LG]

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