{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T17:21:22Z","timestamp":1786209682089,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,1,20]],"date-time":"2020-01-20T00:00:00Z","timestamp":1579478400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["61772310,61702300,61702302,61802231,U1836216,61902219"],"award-info":[{"award-number":["61772310,61702300,61702302,61802231,U1836216,61902219"]}]},{"name":"the Future Talents Research Funds of Shandong University","award":["2018WLJH63"],"award-info":[{"award-number":["2018WLJH63"]}]},{"name":"the Fundamental Research Funds of Shandong University"},{"name":"the Shandong Provincial Natural Science and Foundation","award":["ZR2019JQ23,ZR2019QF001"],"award-info":[{"award-number":["ZR2019JQ23,ZR2019QF001"]}]},{"name":"the Tencent AI Lab Rhino-Bird Focused Research Program","award":["JR201932"],"award-info":[{"award-number":["JR201932"]}]},{"name":"the Project of Thousand Youth Talents 2016"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,1,20]]},"DOI":"10.1145\/3336191.3371805","type":"proceedings-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T19:08:16Z","timestamp":1579720096000},"page":"582-590","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":51,"title":["LARA"],"prefix":"10.1145","author":[{"given":"Changfeng","family":"Sun","sequence":"first","affiliation":[{"name":"Shandong University & Pengcheng Laboratory, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Liu","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Liu","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaochun","family":"Ren","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian","family":"Gan","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liqiang","family":"Nie","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aci.2014.10.001"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-012-0083-7"},{"key":"e_1_3_2_1_4_1","volume-title":"Wasserstein Generative Adversarial Networks. In International Conference on Machine Learning. PMLR, 214--223","author":"Arjovsky Martin","year":"2017"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271743"},{"key":"e_1_3_2_1_6_1","volume-title":"Advances in Neural Information Processing Systems. Curran Associates","author":"Chen Wei"},{"key":"e_1_3_2_1_7_1","unstructured":"Emily L Denton Soumith Chintala Rob Fergus etal 2015. Deep Generative Image Models Using a Laplacian Pyramid of Adversarial Networks. In Advances in Neural Information Processing Systems. 1486--1494.  Emily L Denton Soumith Chintala Rob Fergus et al. 2015. Deep Generative Image Models Using a Laplacian Pyramid of Adversarial Networks. In Advances in Neural Information Processing Systems. 1486--1494."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271768"},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of the 19th International Society for Music Information Retrieval Conference. ISMIR, 190--196","author":"Dong Hao-Wen","year":"2018"},{"key":"e_1_3_2_1_10_1","volume-title":"MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment. In Thirty-Second AAAI Conference on Artificial Intelligence. AAAI, 34--41","author":"Dong Hao-Wen","year":"2018"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-017-9295-9"},{"key":"e_1_3_2_1_12_1","volume-title":"Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. In The 10th IEEE International Conference on Data Mining. IEEE, 176--185","author":"Gantner Zeno","year":"2010"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. JMLR.org, 249--256","author":"Glorot Xavier","year":"2010"},{"key":"e_1_3_2_1_14_1","volume-title":"Advances in Neural Information Processing Systems","author":"Goodfellow Ian"},{"key":"e_1_3_2_1_15_1","volume-title":"Thirty-Second AAAI Conference on Artificial Intelligence. AAAI, 5141--5148","author":"Guo Jiaxian","year":"2018"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350950"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.045"},{"key":"e_1_3_2_1_23_1","unstructured":"Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial nets. arXiv preprint arXiv:1411.1784 (2014) 1--7.  Mehdi Mirza and Simon Osindero. 2014. Conditional Generative Adversarial nets. arXiv preprint arXiv:1411.1784 (2014) 1--7."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1639714.1639720"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983323.2983839"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372071"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2645710.2645751"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"J Ben Schafer Joseph A Konstan and John Riedl. 2001. E-commerce recommendation applications. Data mining and knowledge discovery 5 1--2 (2001) 115--153.  J Ben Schafer Joseph A Konstan and John Riedl. 2001. E-commerce recommendation applications. Data mining and knowledge discovery 5 1--2 (2001) 115--153.","DOI":"10.1023\/A:1009804230409"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/564376.564421"},{"key":"e_1_3_2_1_30_1","unstructured":"Michael Shekasta Gilad Katz Asnat Greenstein-Messica Lior Rokach and Bracha Shapira. 2019. New Item Consumption Prediction Using Deep Learning. arXiv preprint arXiv:1905.01686 (2019) 1--9.  Michael Shekasta Gilad Katz Asnat Greenstein-Messica Lior Rokach and Bracha Shapira. 2019. New Item Consumption Prediction Using Deep Learning. arXiv preprint arXiv:1905.01686 (2019) 1--9."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271730"},{"key":"e_1_3_2_1_32_1","volume-title":"Graphgan: Graph Representation Learning with Generative Adversarial Nets. In Thirty-Second AAAI Conference on Artificial Intelligence. AAAI, 2508--2515","author":"Wang Hongwei","year":"2018"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/618"},{"key":"e_1_3_2_1_35_1","volume-title":"KGAT: Knowledge Graph Attention Network for Recommendation. arXiv preprint arXiv:1905.07854","author":"He Xiangnan","year":"2019"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186066"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 185--194","author":"He Xiangnan","year":"2017"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.09.040"},{"key":"e_1_3_2_1_39_1","unstructured":"Hong-Jian Xue Xinyu Dai Jianbing Zhang Shujian Huang and Jiajun Chen. 2017. Deep Matrix Factorization Models for Recommender Systems.. In IJCAI. 3203--3209.  Hong-Jian Xue Xinyu Dai Jianbing Zhang Shujian Huang and Jiajun Chen. 2017. Deep Matrix Factorization Models for Recommender Systems.. In IJCAI. 3203--3209."},{"key":"e_1_3_2_1_40_1","first-page":"46411","article-title":"Image Inpainting Based on Patch-GANs","volume":"7","author":"Yuan Liuchun","year":"2019","journal-title":"Institute of Electrical and Electronics Engineers Access"},{"key":"e_1_3_2_1_41_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning. PMLR, 4006--4015","author":"Zhang Yizhe","year":"2017"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2009916.2009961"}],"event":{"name":"WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining","location":"Houston TX USA","acronym":"WSDM '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 13th International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371805","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3336191.3371805","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:10Z","timestamp":1750206370000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371805"}},"subtitle":["Attribute-to-feature Adversarial Learning for New-item Recommendation"],"short-title":[],"issued":{"date-parts":[[2020,1,20]]},"references-count":42,"alternative-id":["10.1145\/3336191.3371805","10.1145\/3336191"],"URL":"https:\/\/doi.org\/10.1145\/3336191.3371805","relation":{},"subject":[],"published":{"date-parts":[[2020,1,20]]},"assertion":[{"value":"2020-01-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}