{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:14:39Z","timestamp":1750306479838,"version":"3.41.0"},"reference-count":35,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2016,7,20]],"date-time":"2016-07-20T00:00:00Z","timestamp":1468972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61502307 and 61170077"],"award-info":[{"award-number":["61502307 and 61170077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"crossref","award":["2014A030310268 and 2016A030313038"],"award-info":[{"award-number":["2014A030310268 and 2016A030313038"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Hong Kong CERG projects","award":["16211214 and 16209715"],"award-info":[{"award-number":["16211214 and 16209715"]}]},{"name":"Natural Science Foundation of SZU","award":["201436"],"award-info":[{"award-number":["201436"]}]},{"name":"China National 973 project","award":["2014CB340304"],"award-info":[{"award-number":["2014CB340304"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Interact. Intell. Syst."],"published-print":{"date-parts":[[2016,8,3]]},"abstract":"<jats:p>Users\u2019 online behaviors such as ratings and examination of items are recognized as one of the most valuable sources of information for learning users\u2019 preferences in order to make personalized recommendations. But most previous works focus on modeling only one type of users\u2019 behaviors such as numerical ratings or browsing records, which are referred to as explicit feedback and implicit feedback, respectively. In this article, we study a Semisupervised Collaborative Recommendation (SSCR) problem with labeled feedback (for explicit feedback) and unlabeled feedback (for implicit feedback), in analogy to the well-known Semisupervised Learning (SSL) setting with labeled instances and unlabeled instances. SSCR is associated with two fundamental challenges, that is, heterogeneity of two types of users\u2019 feedback and uncertainty of the unlabeled feedback. As a response, we design a novel Self-Transfer Learning (sTL) algorithm to iteratively identify and integrate likely positive unlabeled feedback, which is inspired by the general forward\/backward process in machine learning. The merit of sTL is its ability to learn users\u2019 preferences from heterogeneous behaviors in a joint and selective manner. We conduct extensive empirical studies of sTL and several very competitive baselines on three large datasets. The experimental results show that our sTL is significantly better than the state-of-the-art methods.<\/jats:p>","DOI":"10.1145\/2835497","type":"journal-article","created":{"date-parts":[[2016,7,21]],"date-time":"2016-07-21T15:13:24Z","timestamp":1469114004000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Transfer Learning for Semisupervised Collaborative Recommendation"],"prefix":"10.1145","volume":"6","author":[{"given":"Weike","family":"Pan","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"}]},{"given":"Qiang","family":"Yang","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, China"}]},{"given":"Yuchao","family":"Duan","sequence":"additional","affiliation":[{"name":"Shenzhen University, Shenzhen, China"}]},{"given":"Zhong","family":"Ming","sequence":"additional","affiliation":[{"name":"Shenzhen University, Shenzhen, China"}]}],"member":"320","published-online":{"date-parts":[[2016,7,20]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/1248547.1248632"},{"key":"e_1_2_1_3_1","volume-title":"Semi-Supervised Learning","author":"Chapelle Olivier","unstructured":"Olivier Chapelle , Bernhard Schlkopf , and Alexander Zien . 2010. Semi-Supervised Learning ( 1 st ed.). The MIT Press . Olivier Chapelle, Bernhard Schlkopf, and Alexander Zien. 2010. Semi-Supervised Learning (1st ed.). The MIT Press.","edition":"1"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273521"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963776"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Christian Desrosiers and George Karypis. 2011. A comprehensive survey of neighborhood-based recommendation methods. In Recommender Systems Handbook. 107--144.  Christian Desrosiers and George Karypis. 2011. A comprehensive survey of neighborhood-based recommendation methods. In Recommender Systems Handbook. 107--144.","DOI":"10.1007\/978-0-387-85820-3_4"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2700495"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/138859.138867"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the 29th AAAI Conference on Artificial Intelligence. 123--129","author":"Guo Guibing","year":"2015","unstructured":"Guibing Guo , Jie Zhang , and Neil Yorke-Smith . 2015 . TrustSVD: Collaborative filtering with both the explicit and implicit influence of user trust and of item ratings . In Proceedings of the 29th AAAI Conference on Artificial Intelligence. 123--129 . Guibing Guo, Jie Zhang, and Neil Yorke-Smith. 2015. TrustSVD: Collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In Proceedings of the 29th AAAI Conference on Artificial Intelligence. 123--129."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2512208"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487589"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_2_1_13_1","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1109\/TCYB.2014.2343982","article-title":"Rating knowledge sharing in cross-domain collaborative filtering","volume":"45","author":"Li Bin","year":"2015","unstructured":"Bin Li , Xingquan Zhu , Ruijiang Li , and Chengqi Zhang . 2015 . Rating knowledge sharing in cross-domain collaborative filtering . IEEE Transactions on Cybernetics 45 , 5 (2015), 1054 -- 1068 . Bin Li, Xingquan Zhu, Ruijiang Li, and Chengqi Zhang. 2015. Rating knowledge sharing in cross-domain collaborative filtering. IEEE Transactions on Cybernetics 45, 5 (2015), 1054--1068.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"e_1_2_1_14_1","volume-title":"Proceedings of the Workshop on \u201cBeyond the Turing Test\u201d of AAAI Conference on Artificial Intelligence.","author":"Li Lianghao","year":"2015","unstructured":"Lianghao Li and Qiang Yang . 2015 . Lifelong machine learning test . In Proceedings of the Workshop on \u201cBeyond the Turing Test\u201d of AAAI Conference on Artificial Intelligence. Lianghao Li and Qiang Yang. 2015. Lifelong machine learning test. In Proceedings of the Workshop on \u201cBeyond the Turing Test\u201d of AAAI Conference on Artificial Intelligence."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2362525"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871643"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.97"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.16"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.11.059"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.05.009"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2014.2"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2015.10.044"},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI\u201912)","author":"Pan Weike","year":"2012","unstructured":"Weike Pan , Evan Wei Xiang , and Qiang Yang . 2012 . Transfer learning in collaborative filtering with uncertain ratings . In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI\u201912) . 662--668. Weike Pan, Evan Wei Xiang, and Qiang Yang. 2012. Transfer learning in collaborative filtering with uncertain ratings. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI\u201912). 662--668."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2013.01.003"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168771"},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI\u201909)","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2009 . BPR: Bayesian personalized ranking from implicit feedback . In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI\u201909) . 452--461. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI\u201909). 452--461."},{"key":"e_1_2_1_28_1","volume-title":"Annual Conference on Neural Information Processing Systems 20","author":"Salakhutdinov Ruslan","year":"2008","unstructured":"Ruslan Salakhutdinov and Andriy Mnih . 2008 . Probabilistic matrix factorization . In Annual Conference on Neural Information Processing Systems 20 . 1257--1264. Ruslan Salakhutdinov and Andriy Mnih. 2008. Probabilistic matrix factorization. In Annual Conference on Neural Information Processing Systems 20. 1257--1264."},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2330900"},{"key":"e_1_2_1_30_1","volume-title":"Proceedings of the Spring Symposium of 2013 AAAI Conference on Artificial Intelligence.","author":"Silver Daniel L.","year":"2013","unstructured":"Daniel L. Silver , Qiang Yang , and Lianghao Li . 2013 . Lifelong machine learning systems: Beyond learning algorithms . In Proceedings of the Spring Symposium of 2013 AAAI Conference on Artificial Intelligence. Daniel L. Silver, Qiang Yang, and Lianghao Li. 2013. Lifelong machine learning systems: Beyond learning algorithms. In Proceedings of the Spring Symposium of 2013 AAAI Conference on Artificial Intelligence."},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-013-0141-9"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-008-5073-7"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2009916.2009959"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2523068"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2015.2465959"}],"container-title":["ACM Transactions on Interactive Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2835497","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2835497","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:48:20Z","timestamp":1750225700000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2835497"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,20]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2016,8,3]]}},"alternative-id":["10.1145\/2835497"],"URL":"https:\/\/doi.org\/10.1145\/2835497","relation":{},"ISSN":["2160-6455","2160-6463"],"issn-type":[{"type":"print","value":"2160-6455"},{"type":"electronic","value":"2160-6463"}],"subject":[],"published":{"date-parts":[[2016,7,20]]},"assertion":[{"value":"2015-07-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-01-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-07-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}