Solving Diversity-Aware Maximum Inner Product Search Efficiently and Effectively-Reference-Cited by-同舟云学术

Solving Diversity-Aware Maximum Inner Product Search Efficiently and Effectively

Published:2022-09-18 Issue: Volume: Page:
ISSN:
Container-title:Sixteenth ACM Conference on Recommender Systems
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Author:

Hirata Kohei¹,Amagata Daichi¹,Fujita Sumio²,Hara Takahiro¹

Affiliation:

1. Osaka University, Japan

2. Yahoo Japan Corporation, Japan

Publisher

ACM

Reference54 articles.

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2. Daichi Amagata and Takahiro Hara. 2016. Diversified set monitoring over distributed data streams. In DEBS. 1–12. Daichi Amagata and Takahiro Hara. 2016. Diversified set monitoring over distributed data streams. In DEBS. 1–12.

3. Daichi Amagata and Takahiro Hara. 2021. Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item?. In RecSys. 273–281. Daichi Amagata and Takahiro Hara. 2021. Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item?. In RecSys. 273–281.

4. Ashton Anderson , Lucas Maystre , Ian Anderson , Rishabh Mehrotra , and Mounia Lalmas . 2020 . Algorithmic Effects on the Diversity of Consumption on Spotify. In The Web Conference. 2155–2165 . Ashton Anderson, Lucas Maystre, Ian Anderson, Rishabh Mehrotra, and Mounia Lalmas. 2020. Algorithmic Effects on the Diversity of Consumption on Spotify. In The Web Conference. 2155–2165.

5. Vito Walter Anelli Alejandro Bellogín Tommaso Di Noia and Claudio Pomo. 2021. Reenvisioning the Comparison between Neural Collaborative Filtering and Matrix Factorization. In RecSys. 521–529. Vito Walter Anelli Alejandro Bellogín Tommaso Di Noia and Claudio Pomo. 2021. Reenvisioning the Comparison between Neural Collaborative Filtering and Matrix Factorization. In RecSys. 521–529.

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1. Curse of "Low" Dimensionality in Recommender Systems;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

2. Simpler is Much Faster: Fair and Independent Inner Product Search;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

3. Reverse Maximum Inner Product Search: Formulation, Algorithms, and Analysis;ACM Transactions on the Web;2023-07-11

4. SMONAC: Supervised Multiobjective Negative Actor–Critic for Sequential Recommendation;IEEE Transactions on Neural Networks and Learning Systems;2023

5. Categorical Diversity-Aware Inner Product Search;IEEE Access;2023