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Since context is often represented by dynamic and high-dimensional feature space in multiple applications and services, we suggest to model contextual information in various ways for multiple purposes, such as rating prediction, generating top-k recommendations, and classification of users\u2019 feedback. Specifically, based on the suggested framework, we propose three deep context-aware recommendation models based on explicit, unstructured, and structured latent representations of contextual data derived from various contextual dimensions (e.g., time, location, user activity). Offline evaluation on three context-aware datasets confirms that our proposed deep context-aware models surpass state-of-the-art context-aware methods. We also show that utilizing structured latent contexts in the proposed deep recommendation framework achieves significantly better performance than the other context-aware models on all datasets.<\/jats:p>","DOI":"10.1145\/3386243","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T22:08:48Z","timestamp":1590444528000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":74,"title":["Context-Aware Recommendations Based on Deep Learning Frameworks"],"prefix":"10.1145","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5512-0331","authenticated-orcid":false,"given":"Moshe","family":"Unger","sequence":"first","affiliation":[{"name":"New York University, New York, NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Tuzhilin","sequence":"additional","affiliation":[{"name":"New York University, New York, NY"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amit","family":"Livne","sequence":"additional","affiliation":[{"name":"Ben-Gurion University of the Negev"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,5,22]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v32i3.2364"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"e_1_2_2_3_1","volume-title":"Recommender Systems Handbook","author":"Adomavicius Gediminas","unstructured":"Gediminas Adomavicius and Alexander Tuzhilin. 2015. 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