V-Elliot: Design, Evaluate and Tune Visual Recommender Systems-Reference-Cited by-同舟云学术

V-Elliot: Design, Evaluate and Tune Visual Recommender Systems

Published:2021-09-13 Issue: Volume: Page:
ISSN:
Container-title:Fifteenth ACM Conference on Recommender Systems
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Author:

Anelli Vito Walter¹,Bellogín Alejandro²,Ferrara Antonio¹,Malitesta Daniele¹,Merra Felice Antonio¹,Pomo Claudio¹,Donini Francesco Maria³,Di Noia Tommaso¹

Affiliation:

1. Politecnico di Bari, Italy

2. Universidad Autonoma de Madrid, Spain

3. Università della Tuscia, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3460231.3478881

Reference30 articles.

1. Vito Walter Anelli Yashar Deldjoo Tommaso Di Noia Daniele Malitesta and Felice Antonio Merra. 2021. A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. In SIGIR. ACM 1094–1103. Vito Walter Anelli Yashar Deldjoo Tommaso Di Noia Daniele Malitesta and Felice Antonio Merra. 2021. A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. In SIGIR. ACM 1094–1103.

2. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. In SIGIR. ACM 335–344. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. In SIGIR. ACM 335–344.

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