A hierarchical attention model for rating prediction by leveraging user and product reviews-Reference-Cited by-同舟云学术

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A hierarchical attention model for rating prediction by leveraging user and product reviews

Published:2019-03 Issue: Volume:332 Page:417-427
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Xing Shuning^ORCID,Liu Fang’ai,Wang Qianqian,Zhao Xiaohui,Li Tianlai

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference41 articles.

1. Matrix factorization techniques for recommender systems;Koren;Computer,2009

2. Collaborative topic modeling for recommending scientific articles;Wang,2011

3. Topicmf: simultaneously exploiting ratings and reviews for recommendation;Bao,2014

4. Rating-boosted latent topics: understanding users and items with ratings and reviews;Tan,2016

5. Latent dirichlet allocation;Blei;J. Mach. Learn. Res.,2003

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