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Intuitively, users\u2019 opinions toward different aspects of an item determine their ratings (i.e., users\u2019 preferences) for the item. Therefore, rating prediction from the perspective of opinions can realize personalized explanations at the level of item aspects and user preferences. However, there are several challenges in developing an opinion-based explainable recommendation: (1) The complicated relationship between users\u2019 opinions and ratings. (2) The difficulty of predicting the potential (i.e., unseen) user-item opinions because of the sparsity of opinion information. To tackle these challenges, we propose an\n            <jats:bold>overall preference-aware opinion-based explainable rating prediction<\/jats:bold>\n            model by jointly modeling the multiple observations of user-item interaction (i.e., review, opinion, rating). To alleviate the sparsity problem and raise the effectiveness of opinion prediction, we further propose a\n            <jats:bold>triple dual learning-based framework with a novelly designed triple dual constraint<\/jats:bold>\n            . Finally, experiments on three popular datasets show the effectiveness and great explanation performance of our framework.\n          <\/jats:p>","DOI":"10.1145\/3631521","type":"journal-article","created":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T22:19:01Z","timestamp":1698963541000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Triple Dual Learning for Opinion-based Explainable Recommendation"],"prefix":"10.1145","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8698-6142","authenticated-orcid":false,"given":"Yuting","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4763-6060","authenticated-orcid":false,"given":"Ying","family":"Sun","sequence":"additional","affiliation":[{"name":"Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9170-7009","authenticated-orcid":false,"given":"Fuzhen","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Beihang University, China and Zhongguancun Laboratory, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7096-3190","authenticated-orcid":false,"given":"Yongchun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7593-8293","authenticated-orcid":false,"given":"Zhulin","family":"An","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6647-0986","authenticated-orcid":false,"given":"Yongjun","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,12,30]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"153","volume-title":"Proceedings of the Beyond Personalization Workshop of the International Conference on Intelligent User Interfaces (IUI\u201905)","volume":"5","author":"Bilgic Mustafa","year":"2005","unstructured":"Mustafa Bilgic and Raymond J. 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