Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation-Reference-Cited by-同舟云学术

Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation

Published:2022-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Lin Zihan¹,Wang Hui¹,Mao Jingshu²,Zhao Wayne Xin³,Wang Cheng²,Jiang Peng²,Wen Ji-Rong³

Affiliation:

1. Renmin University of China, Beijing, China

2. Kuaishou Inc., Beijing, China

3. Renmin University of China, Beijing Key Laboratory of Big Data Management and Analysis Methods, & Beijing Academy of Artificial Intelligence, Beijing, China

Funder

Beijing Outstanding Young Scientist Program

Beijing Natural Sci- ence Foundation

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539130

Reference45 articles.

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3. The use of MMR, diversity-based reranking for reordering documents and producing summaries

4. Decomposed Collaborative Filtering;Chen Hao;Modeling Explicit and Implicit Factors For Recommender Systems. In WWW,2021

5. Laming Chen , Guoxin Zhang , and Hanning Zhou . 2018 . Fast greedy map inference for determinantal point process to improve recommendation diversity . In NIPS 2018. 5627--5638. Laming Chen, Guoxin Zhang, and Hanning Zhou. 2018. Fast greedy map inference for determinantal point process to improve recommendation diversity. In NIPS 2018. 5627--5638.

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