LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup-Reference-Cited by-同舟云学术

LOAM: Improving Long-tail Session-based Recommendation via Niche Walk Augmentation and Tail Session Mixup

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Yang Heeyoon¹^ORCID,Choi YunSeok¹^ORCID,Kim Gahyung¹^ORCID,Lee Jee-Hyong¹^ORCID

Affiliation:

1. Sungkyunkwan University, Suwon, Republic of Korea

Funder

ICT Creative Consilience Program by MSIT

AI Graduate School Support Program(Sungkyunkwan University) by MSIT

Self-directed Multi-modal Intelligence for solving unknown, open domain problems by MSIT

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591718

Reference35 articles.

1. C. Anderson . 2006. The Long Tail: Why the Future of Business Is Selling Less of More . Hachette Books . https://books.google.co.kr/books?id=DTeZAAAAQBAJ C. Anderson. 2006. The Long Tail: Why the Future of Business Is Selling Less of More. Hachette Books. https://books.google.co.kr/books?id=DTeZAAAAQBAJ

2. DLTSR: A Deep Learning Framework for Recommendations of Long-Tail Web Services

3. Tianwen Chen and Raymond Chi-Wing Wong . 2020 . Handling Information Loss of Graph Neural Networks for Session-based Recommendation. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , Virtual Event, CA, USA , August 23-27, 2020. ACM, 1172--1180. https://dl.acm.org/doi/10.1145/3394486.3403170 Tianwen Chen and Raymond Chi-Wing Wong. 2020. Handling Information Loss of Graph Neural Networks for Session-based Recommendation. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM, 1172--1180. https://dl.acm.org/doi/10.1145/3394486.3403170

4. Remix: Rebalanced Mixup

5. Data Augmentation for Deep Neural Network Acoustic Modeling

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