A Two-tier Shared Embedding Method for Review-based Recommender Systems-Reference-Cited by-同舟云学术

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A Two-tier Shared Embedding Method for Review-based Recommender Systems

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
language:
Short-container-title:

Author:

Yang Zhen¹^ORCID,Liu Junrui¹^ORCID,Li Tong¹^ORCID,Wu Di¹^ORCID,Yang Shiqiu¹^ORCID,Liu Huan²^ORCID

Affiliation:

1. Beijing University of Technology, Beijing, China

2. Arizona State University, Tempe, AZ, USA

Funder

National Key Research and Development Program of China

Beijing Municipal Education Commission

Beijing Municipal Natural Science Foundation

National Natural Science Foundation of China

Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3614770

Reference50 articles.

1. Enhancing recommendation systems performance using highly-effective similarity measures

2. Improving Collaborative Recommendation via User-Item Subgroups

3. Graph Regularized Nonnegative Matrix Factorization for Data Representation

4. TransNets

5. Neural Attentional Rating Regression with Review-level Explanations

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