{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T20:04:07Z","timestamp":1770494647003,"version":"3.49.0"},"reference-count":33,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T00:00:00Z","timestamp":1642377600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T00:00:00Z","timestamp":1642377600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Int J of Intelligent Sys"],"published-print":{"date-parts":[[2022,5]]},"DOI":"10.1002\/int.22827","type":"journal-article","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T09:37:50Z","timestamp":1642412270000},"page":"3006-3024","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Exploring lottery ticket hypothesis in media recommender systems"],"prefix":"10.1155","volume":"37","author":[{"given":"Yanfang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Science and Technology University of Science and Technology of China Hefei Anhui China"}]},{"given":"Yongduo","family":"Sui","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology University of Science and Technology of China Hefei Anhui China"}]},{"given":"Xiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computing National University of Singapore Kent Ridge Singapore"}]},{"given":"Zhenguang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China"}]},{"given":"Xiangnan","family":"He","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology University of Science and Technology of China Hefei Anhui China"}]}],"member":"311","published-online":{"date-parts":[[2022,1,17]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22412"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22320"},{"key":"e_1_2_8_4_1","doi-asserted-by":"crossref","unstructured":"WangX HeX WangM FengF ChuaTS. Neural graph collaborative filtering. Proceedings of the 42nd international ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR);2019:165\u2010174.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_2_8_5_1","doi-asserted-by":"crossref","unstructured":"HeX DengK WangX LiY ZhangY WangM. Lightgcn: simplifying and powering graph convolution network for recommendation. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR);2020:639\u2010648.","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-018-9654-y"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3158369"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"key":"e_1_2_8_9_1","doi-asserted-by":"crossref","unstructured":"GuptaU HsiaS SaraphV et al. Deeprecsys: a system for optimizing end\u2010to\u2010end at\u2010scale neural recommendation inference. 2020 ACM\/IEEE 47th Annual International Symposium on Computer Architecture (ISCA);2020:982\u2010995.","DOI":"10.1109\/ISCA45697.2020.00084"},{"key":"e_1_2_8_10_1","doi-asserted-by":"crossref","unstructured":"CovingtonP AdamsJ SarginE. Deep neural networks for youtube recommendations. Proceedings of the 10th ACM Conference on Recommender Systems (RecSys);2016:191\u2010198.","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_2_8_11_1","unstructured":"LiuS GaoC ChenY JinD LiY. Learnable embedding sizes for recommender systems. International Conference on Learning Representations (ICLR);2020."},{"key":"e_1_2_8_12_1","unstructured":"FrankleJ CarbinM. The lottery ticket hypothesis: finding sparse trainable neural networks. International Conference on Learning Representations (ICLR);2019."},{"key":"e_1_2_8_13_1","unstructured":"YuH EdunovS TianY MorcosAS. Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. International Conference on Learning Representations (ICLR);2019."},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0686-2"},{"key":"e_1_2_8_15_1","unstructured":"ChenT SuiY ChenX ZhangA WangZ. A unified lottery ticket hypothesis for graph neural networks. In: International Conference on Machine Learning (ICML); 2021:1695\u20101706."},{"key":"e_1_2_8_16_1","unstructured":"RendleS FreudenthalerC GantnerZ Schmidt\u2010ThiemeL. BPR: bayesian personalized ranking from implicit feedback. In: Proceedings of the Twenty\u2010Fifth Conference on Uncertainty in Artificial Intelligence (UAI). Arlington Virginia USA;2009:452\u2010461."},{"key":"e_1_2_8_17_1","doi-asserted-by":"crossref","unstructured":"JoglekarMR LiC ChenM et al. Neural input search for large scale recommendation models. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (SIGKDD);2020:2387\u20102397.","DOI":"10.1145\/3394486.3403288"},{"key":"e_1_2_8_18_1","doi-asserted-by":"crossref","unstructured":"LiuH ZhaoX WangC LiuX TangJ. Automated embedding size search in deep recommender systems. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR);2020:2307\u20102316.","DOI":"10.1145\/3397271.3401436"},{"key":"e_1_2_8_19_1","unstructured":"PhamH GuanM ZophB LeQ DeanJ. Efficient neural architecture search via parameters sharing. International Conference on Machine Learning (ICML);2018:4095\u20104104."},{"key":"e_1_2_8_20_1","unstructured":"LiuH SimonyanK YangY. DARTS: Differentiable architecture search. In: International Conference on Learning Representations (ICLR);2018."},{"issue":"2","key":"e_1_2_8_21_1","first-page":"251","article-title":"Survey of deep neural network model compression","volume":"29","author":"Lei J","year":"2018","journal-title":"J Softw"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2765695"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/int.22302"},{"key":"e_1_2_8_24_1","unstructured":"GuptaS AgrawalA GopalakrishnanK NarayananP. Deep learning with limited numerical precision. International Conference on Machine Learning (ICML);2015:1737\u20101746."},{"key":"e_1_2_8_25_1","doi-asserted-by":"crossref","unstructured":"JiaoX YinY ShangL et al. TinyBERT: Distilling BERT for natural language understanding. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP: Findings);2020:4163\u20104174.","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"e_1_2_8_26_1","doi-asserted-by":"crossref","unstructured":"SunY YuanF YangM WeiG ZhaoZ LiuD. A generic network compression framework for sequential recommender systems. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR);2020:1299\u20101308.","DOI":"10.1145\/3397271.3401125"},{"key":"e_1_2_8_27_1","doi-asserted-by":"crossref","unstructured":"WuX XuH ZhangH ChenH WangJ. Saec: Similarity\u2010aware embedding compression in recommendation systems. Proceedings of the 11th ACM SIGOPS Asia\u2010Pacific Workshop on Systems (APSys);2020:82\u201089.","DOI":"10.1145\/3409963.3410498"},{"key":"e_1_2_8_28_1","doi-asserted-by":"crossref","unstructured":"ZhangC LiuY XieY et al. Model size reduction using frequency based double hashing for recommender systems. Proceedings of the 14th ACM Conference on Recommender Systems (RecSys);2020:521\u2010526.","DOI":"10.1145\/3383313.3412227"},{"key":"e_1_2_8_29_1","doi-asserted-by":"crossref","unstructured":"BrixC BaharP NeyH. Successfully applying the stabilized lottery ticket hypothesis to the transformer architecture. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL);2020:3909\u20103915.","DOI":"10.18653\/v1\/2020.acl-main.360"},{"key":"e_1_2_8_30_1","unstructured":"RendaA FrankleJ CarbinM. Comparing rewinding and fine\u2010tuning in neural network pruning. International Conference on Learning Representations (ICLR);2020."},{"key":"e_1_2_8_31_1","unstructured":"YouH LiC XuP et al. Drawing early\u2010bird tickets: toward more efficient training of deep networks. International Conference on Learning Representations (ICLR);2020."},{"key":"e_1_2_8_32_1","unstructured":"MorcosAS YuH PaganiniM TianY. One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. Proceedings of the 33rd International Conference on Neural Information Processing Systems (NeurIPS);2019:4932\u20104942."},{"key":"e_1_2_8_33_1","doi-asserted-by":"crossref","unstructured":"HeX LiaoL ZhangH NieL HuX ChuaTS. Neural collaborative filtering. Proceedings of the 26th International Conference on World Wide Web (WWW);2017:173\u2010182.","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_2_8_34_1","unstructured":"KingmaDP BaJ. Adam: a method for stochastic optimization. International Conference on Learning Representations (ICLR);2015."}],"container-title":["International Journal of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/int.22827","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/int.22827","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/int.22827","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T13:01:34Z","timestamp":1726491694000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/int.22827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,17]]},"references-count":33,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,5]]}},"alternative-id":["10.1002\/int.22827"],"URL":"https:\/\/doi.org\/10.1002\/int.22827","archive":["Portico"],"relation":{},"ISSN":["0884-8173","1098-111X"],"issn-type":[{"value":"0884-8173","type":"print"},{"value":"1098-111X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,17]]},"assertion":[{"value":"2021-07-31","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-12-29","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-01-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}