Alleviating the Long-Tail Problem in Conversational Recommender Systems-Reference-Cited by-同舟云学术

Alleviating the Long-Tail Problem in Conversational Recommender Systems

Published:2023-09-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 17th ACM Conference on Recommender Systems
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Author:

Zhao Zhipeng¹^ORCID,Zhou Kun²^ORCID,Wang Xiaolei³^ORCID,Zhao Wayne Xin⁴^ORCID,Pan Fan⁵^ORCID,Cao Zhao⁵^ORCID,Wen Ji-Rong⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Institute of Technology, China

2. School of Information, Renmin University of China, China

3. Gaoling School of Artificial Intelligence, Gaoling School of Artificial Intelligence, Renmin University of China, China

4. Gaoling School of Artificial Intelligence, Renmin University of China, China

5. Poisson Lab, Huawei, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604915.3608812

Reference61 articles.

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2. Beyond Globally Optimal

3. Erik Brynjolfsson , Yu Jeffrey Hu , and Michael D Smith . 2006. From niches to riches: Anatomy of the long tail. Sloan management review 47, 4 ( 2006 ), 67–71. Erik Brynjolfsson, Yu Jeffrey Hu, and Michael D Smith. 2006. From niches to riches: Anatomy of the long tail. Sloan management review 47, 4 (2006), 67–71.

4. Qibin Chen Junyang Lin Yichang Zhang Ming Ding Yukuo Cen Hongxia Yang and Jie Tang. 2019. Towards Knowledge-Based Recommender Dialog System. In EMNLP. 1803–1813. Qibin Chen Junyang Lin Yichang Zhang Ming Ding Yukuo Cen Hongxia Yang and Jie Tang. 2019. Towards Knowledge-Based Recommender Dialog System. In EMNLP. 1803–1813.

5. Konstantina Christakopoulou Filip Radlinski and Katja Hofmann. 2016. Towards conversational recommender systems. In KDD. 815–824. Konstantina Christakopoulou Filip Radlinski and Katja Hofmann. 2016. Towards conversational recommender systems. In KDD. 815–824.

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