{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T23:13:21Z","timestamp":1767914001691,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T00:00:00Z","timestamp":1631491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore","doi-asserted-by":"publisher","award":["NRF-NRFF2016-07"],"award-info":[{"award-number":["NRF-NRFF2016-07"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,13]]},"DOI":"10.1145\/3460231.3473324","type":"proceedings-article","created":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T21:45:04Z","timestamp":1631569504000},"page":"834-837","source":"Crossref","is-referenced-by-count":28,"title":["Multi-Modal Recommender Systems: Hands-On Exploration"],"prefix":"10.1145","author":[{"given":"Quoc-Tuan","family":"Truong","sequence":"first","affiliation":[{"name":"School of Information Systems Singapore Management University, Singapore"}]},{"given":"Aghiles","family":"Salah","sequence":"additional","affiliation":[{"name":"Rakuten Institute of Technology, France"}]},{"given":"Hady","family":"Lauw","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems Singapore Management University, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2021,9,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Allison\u00a0JB Chaney David\u00a0M Blei and Tina Eliassi-Rad. 2015. A probabilistic model for using social networks in personalized item recommendation. In RecSys. 43\u201350.  Allison\u00a0JB Chaney David\u00a0M Blei and Tina Eliassi-Rad. 2015. A probabilistic model for using social networks in personalized item recommendation. In RecSys. 43\u201350.","DOI":"10.1145\/2792838.2800193"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335\u2013344.  Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335\u2013344.","DOI":"10.1145\/3077136.3080797"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph neural networks for social recommendation. In WWW. 417\u2013426.  Wenqi Fan Yao Ma Qing Li Yuan He Eric Zhao Jiliang Tang and Dawei Yin. 2019. Graph neural networks for social recommendation. In WWW. 417\u2013426.","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_1_5_1","unstructured":"Ruining He and Julian McAuley. 2016. VBPR: visual bayesian personalized ranking from implicit feedback. In AAAI.  Ruining He and Julian McAuley. 2016. VBPR: visual bayesian personalized ranking from implicit feedback. In AAAI."},{"key":"e_1_3_2_1_6_1","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural collaborative filtering. In WWW. 173\u2013182.  Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural collaborative filtering. In WWW. 173\u2013182."},{"key":"e_1_3_2_1_7_1","unstructured":"Yifan Hu Yehuda Koren and Chris Volinsky. 2008. Collaborative filtering for implicit feedback datasets. In ICDM. 263\u2013272.  Yifan Hu Yehuda Koren and Chris Volinsky. 2008. Collaborative filtering for implicit feedback datasets. In ICDM. 263\u2013272."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Wang-Cheng Kang Chen Fang Zhaowen Wang and Julian McAuley. 2017. Visually-aware fashion recommendation and design with generative image models. In ICDM. 207\u2013216.  Wang-Cheng Kang Chen Fang Zhaowen Wang and Julian McAuley. 2017. Visually-aware fashion recommendation and design with generative image models. In ICDM. 207\u2013216.","DOI":"10.1109\/ICDM.2017.30"},{"key":"e_1_3_2_1_9_1","unstructured":"Donghyun Kim Chanyoung Park Jinoh Oh Sungyoung Lee and Hwanjo Yu. 2016. Convolutional matrix factorization for document context-aware recommendation. In RecSys. 233\u2013240.  Donghyun Kim Chanyoung Park Jinoh Oh Sungyoung Lee and Hwanjo Yu. 2016. Convolutional matrix factorization for document context-aware recommendation. In RecSys. 233\u2013240."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_11_1","unstructured":"Wonsung Lee Kyungwoo Song and Il-Chul Moon. 2017. Augmented variational autoencoders for collaborative filtering with auxiliary information. In CIKM. 1139\u20131148.  Wonsung Lee Kyungwoo Song and Il-Chul Moon. 2017. Augmented variational autoencoders for collaborative filtering with auxiliary information. In CIKM. 1139\u20131148."},{"key":"e_1_3_2_1_12_1","unstructured":"Chenyi Lei Dong Liu Weiping Li Zheng-Jun Zha and Houqiang Li. 2016. Comparative deep learning of hybrid representations for image recommendations. In CVPR. 2545\u20132553.  Chenyi Lei Dong Liu Weiping Li Zheng-Jun Zha and Houqiang Li. 2016. Comparative deep learning of hybrid representations for image recommendations. In CVPR. 2545\u20132553."},{"key":"e_1_3_2_1_13_1","unstructured":"Piji Li Zihao Wang Zhaochun Ren Lidong Bing and Wai Lam. 2017. Neural rating regression with abstractive tips generation for recommendation. In SIGIR.  Piji Li Zihao Wang Zhaochun Ren Lidong Bing and Wai Lam. 2017. Neural rating regression with abstractive tips generation for recommendation. In SIGIR."},{"key":"e_1_3_2_1_14_1","unstructured":"Xiaopeng Li and James She. 2017. Collaborative variational autoencoder for recommender systems. In SIGKDD.  Xiaopeng Li and James She. 2017. Collaborative variational autoencoder for recommender systems. In SIGKDD."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Dawen Liang Rahul\u00a0G Krishnan Matthew\u00a0D Hoffman and Tony Jebara. 2018. Variational autoencoders for collaborative filtering. In WWW.  Dawen Liang Rahul\u00a0G Krishnan Matthew\u00a0D Hoffman and Tony Jebara. 2018. Variational autoencoders for collaborative filtering. In WWW.","DOI":"10.1145\/3178876.3186150"},{"key":"e_1_3_2_1_16_1","unstructured":"Zhongqi Lu Zhicheng Dou Jianxun Lian Xing Xie and Qiang Yang. 2015. Content-based collaborative filtering for news topic recommendation. In AAAI.  Zhongqi Lu Zhicheng Dou Jianxun Lian Xing Xie and Qiang Yang. 2015. Content-based collaborative filtering for news topic recommendation. In AAAI."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Hao Ma Haixuan Yang Michael\u00a0R Lyu and Irwin King. 2008. Sorec: social recommendation using probabilistic matrix factorization. In CIKM. 931\u2013940.  Hao Ma Haixuan Yang Michael\u00a0R Lyu and Irwin King. 2008. Sorec: social recommendation using probabilistic matrix factorization. In CIKM. 931\u2013940.","DOI":"10.1145\/1458082.1458205"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Hao Ma Dengyong Zhou Chao Liu Michael\u00a0R Lyu and Irwin King. 2011. Recommender systems with social regularization. In WSDM. 287\u2013296.  Hao Ma Dengyong Zhou Chao Liu Michael\u00a0R Lyu and Irwin King. 2011. Recommender systems with social regularization. In WSDM. 287\u2013296.","DOI":"10.1145\/1935826.1935877"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Julian McAuley and Jure Leskovec. 2013. Hidden factors and hidden topics: understanding rating dimensions with review text. In RecSys. 165\u2013172.  Julian McAuley and Jure Leskovec. 2013. Hidden factors and hidden topics: understanding rating dimensions with review text. In RecSys. 165\u2013172.","DOI":"10.1145\/2507157.2507163"},{"key":"e_1_3_2_1_20_1","unstructured":"Andriy Mnih and Russ\u00a0R Salakhutdinov. 2008. Probabilistic matrix factorization. In NIPS. 1257\u20131264.  Andriy Mnih and Russ\u00a0R Salakhutdinov. 2008. Probabilistic matrix factorization. In NIPS. 1257\u20131264."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959157"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Wei Niu James Caverlee and Haokai Lu. 2018. Neural personalized ranking for image recommendation. In WSDM. 423\u2013431.  Wei Niu James Caverlee and Haokai Lu. 2018. Neural personalized ranking for image recommendation. In WSDM. 423\u2013431.","DOI":"10.1145\/3159652.3159728"},{"key":"e_1_3_2_1_23_1","first-page":"1113","article-title":"Do","author":"Park Chanyoung","year":"2017","unstructured":"Chanyoung Park , Donghyun Kim , Jinoh Oh , and Hwanjo Yu . 2017 . Do \u201d Also-Viewed\u201d Products Help User Rating Prediction?. In WWW. 1113 \u2013 1122 . Chanyoung Park, Donghyun Kim, Jinoh Oh, and Hwanjo Yu. 2017. Do\u201d Also-Viewed\u201d Products Help User Rating Prediction?. In WWW. 1113\u20131122.","journal-title":"Products Help User Rating Prediction?. In WWW."},{"key":"e_1_3_2_1_24_1","unstructured":"Rendle S. Freudenthaler C. Gantner Z. and Schmidt-Thieme L.2012. BPR: Bayesian personalized ranking from implicit feedback. In UAI.  Rendle S. Freudenthaler C. Gantner Z. and Schmidt-Thieme L.2012. BPR: Bayesian personalized ranking from implicit feedback. In UAI."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Aghiles Salah and Hady\u00a0W Lauw. 2018. A bayesian latent variable model of user preferences with item context. IJCAI.  Aghiles Salah and Hady\u00a0W Lauw. 2018. A bayesian latent variable model of user preferences with item context. IJCAI.","DOI":"10.24963\/ijcai.2018\/370"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Aghiles Salah and Hady\u00a0W Lauw. 2018. Probabilistic collaborative representation learning for personalized item recommendation. In UAI.  Aghiles Salah and Hady\u00a0W Lauw. 2018. Probabilistic collaborative representation learning for personalized item recommendation. In UAI.","DOI":"10.24963\/ijcai.2017\/286"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-017-0499-9"},{"key":"e_1_3_2_1_28_1","first-page":"95","article-title":"Cornac: A Comparative Framework for Multimodal Recommender Systems.","volume":"21","author":"Salah Aghiles","year":"2020","unstructured":"Aghiles Salah , Quoc-Tuan Truong , and Hady\u00a0 W Lauw . 2020 . Cornac: A Comparative Framework for Multimodal Recommender Systems. JMLR 21 (2020), 95 \u2013 91 . Aghiles Salah, Quoc-Tuan Truong, and Hady\u00a0W Lauw. 2020. Cornac: A Comparative Framework for Multimodal Recommender Systems.JMLR 21(2020), 95\u20131.","journal-title":"JMLR"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Ajit\u00a0P Singh and Geoffrey\u00a0J Gordon. 2008. Relational learning via collective matrix factorization. In SIGKDD. 650\u2013658.  Ajit\u00a0P Singh and Geoffrey\u00a0J Gordon. 2008. Relational learning via collective matrix factorization. In SIGKDD. 650\u2013658.","DOI":"10.21236\/ADA486804"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Quoc-Tuan Truong and Hady Lauw. 2019. Multimodal review generation for recommender systems. In WWW. 1864\u20131874.  Quoc-Tuan Truong and Hady Lauw. 2019. Multimodal review generation for recommender systems. In WWW. 1864\u20131874.","DOI":"10.1145\/3308558.3313463"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Quoc-Tuan Truong Aghiles Salah and Hady\u00a0W Lauw. 2021. Bilateral Variational Autoencoder for Collaborative Filtering. In WSDM. 292\u2013300.  Quoc-Tuan Truong Aghiles Salah and Hady\u00a0W Lauw. 2021. Bilateral Variational Autoencoder for Collaborative Filtering. In WSDM. 292\u2013300.","DOI":"10.1145\/3437963.3441759"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2021.3059027"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Dashun Wang Dino Pedreschi Chaoming Song Fosca Giannotti and Albert-Laszlo Barabasi. 2011. Human mobility social ties and link prediction. In SIGKDD. 1100\u20131108.  Dashun Wang Dino Pedreschi Chaoming Song Fosca Giannotti and Albert-Laszlo Barabasi. 2011. Human mobility social ties and link prediction. In SIGKDD. 1100\u20131108.","DOI":"10.1145\/2020408.2020581"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Hao Wang Naiyan Wang and Dit-Yan Yeung. 2015. Collaborative deep learning for recommender systems. In SIGKDD.  Hao Wang Naiyan Wang and Dit-Yan Yeung. 2015. Collaborative deep learning for recommender systems. In SIGKDD.","DOI":"10.1145\/2783258.2783273"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Suhang Wang Yilin Wang Jiliang Tang Kai Shu Suhas Ranganath and Huan Liu. 2017. What your images reveal: Exploiting visual contents for point-of-interest recommendation. In WWW. 391\u2013400.  Suhang Wang Yilin Wang Jiliang Tang Kai Shu Suhas Ranganath and Huan Liu. 2017. What your images reveal: Exploiting visual contents for point-of-interest recommendation. In WWW. 391\u2013400.","DOI":"10.1145\/3038912.3052638"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_1_37_1","unstructured":"Weilong Yao Jing He Hua Wang Yanchun Zhang and Jie Cao. 2015. Collaborative topic ranking: Leveraging item meta-data for sparsity reduction. In AAAI.  Weilong Yao Jing He Hua Wang Yanchun Zhang and Jie Cao. 2015. Collaborative topic ranking: Leveraging item meta-data for sparsity reduction. In AAAI."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Haochao Ying Liang Chen Yuwen Xiong and Jian Wu. 2016. Collaborative deep ranking: A hybrid pair-wise recommendation algorithm with implicit feedback. In PAKDD.  Haochao Ying Liang Chen Yuwen Xiong and Jian Wu. 2016. Collaborative deep ranking: A hybrid pair-wise recommendation algorithm with implicit feedback. In PAKDD.","DOI":"10.1007\/978-3-319-31750-2_44"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Fuzheng Zhang Nicholas\u00a0Jing Yuan Defu Lian Xing Xie and Wei-Ying Ma. 2016. Collaborative knowledge base embedding for recommender systems. In SIGKDD. 353\u2013362.  Fuzheng Zhang Nicholas\u00a0Jing Yuan Defu Lian Xing Xie and Wei-Ying Ma. 2016. Collaborative knowledge base embedding for recommender systems. In SIGKDD. 353\u2013362.","DOI":"10.1145\/2939672.2939673"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Shuai Zhang Lina Yao and Xiwei Xu. 2017. Autosvd++ an efficient hybrid collaborative filtering model via contractive auto-encoders. In SIGIR.  Shuai Zhang Lina Yao and Xiwei Xu. 2017. Autosvd++ an efficient hybrid collaborative filtering model via contractive auto-encoders. In SIGIR.","DOI":"10.1145\/3077136.3080689"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Yongfeng Zhang Qingyao Ai Xu Chen and W\u00a0Bruce Croft. 2017. Joint representation learning for top-n recommendation with heterogeneous information sources. In CIKM. 1449\u20131458.  Yongfeng Zhang Qingyao Ai Xu Chen and W\u00a0Bruce Croft. 2017. Joint representation learning for top-n recommendation with heterogeneous information sources. In CIKM. 1449\u20131458.","DOI":"10.1145\/3132847.3132892"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Lei Zheng Vahid Noroozi and Philip\u00a0S Yu. 2017. Joint deep modeling of users and items using reviews for recommendation. In WSDM.  Lei Zheng Vahid Noroozi and Philip\u00a0S Yu. 2017. Joint deep modeling of users and items using reviews for recommendation. In WSDM.","DOI":"10.1145\/3018661.3018665"}],"event":{"name":"RecSys '21: Fifteenth ACM Conference on Recommender Systems","location":"Amsterdam Netherlands","acronym":"RecSys '21","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGAI ACM Special Interest Group on Artificial Intelligence","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval","SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGecom Special Interest Group on Economics and Computation"]},"container-title":["Fifteenth ACM Conference on Recommender Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460231.3473324","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3460231.3473324","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:17Z","timestamp":1750191137000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460231.3473324"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,13]]},"references-count":42,"alternative-id":["10.1145\/3460231.3473324","10.1145\/3460231"],"URL":"https:\/\/doi.org\/10.1145\/3460231.3473324","relation":{},"subject":[],"published":{"date-parts":[[2021,9,13]]}}}