{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T07:57:10Z","timestamp":1778313430222,"version":"3.51.4"},"reference-count":46,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2020,6,16]],"date-time":"2020-06-16T00:00:00Z","timestamp":1592265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100010246","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M611322"],"award-info":[{"award-number":["2017M611322"]}],"id":[{"id":"10.13039\/501100010246","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Changchun Science and Technology Development Project","award":["18DY005"],"award-info":[{"award-number":["18DY005"]}]},{"DOI":"10.13039\/501100012659","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772230"],"award-info":[{"award-number":["61772230"]}],"id":[{"id":"10.13039\/501100012659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2020,8,31]]},"abstract":"<jats:p>\n            Recommender systems have been playing an important role in providing personalized information to users. However, there is always a trade-off between accuracy and novelty in recommender systems. Usually, many users are suffering from redundant or inaccurate recommendation results. To this end, in this article, we put efforts into exploring the hidden knowledge of observed ratings to alleviate this recommendation dilemma. Specifically, we utilize some basic concepts to define a concept,\n            <jats:italic>Serendipity<\/jats:italic>\n            , which is characterized by high-satisfaction and low-initial-interest. Based on this concept, we propose a two-phase recommendation problem which aims to strike a balance between accuracy and novelty achieved by serendipity prediction and personalized recommendation. Along this line, a Neural Serendipity Recommendation (NSR) method is first developed by combining Muti-Layer Percetron and Matrix Factorization for serendipity prediction. Then, a weighted candidate filtering method is designed for personalized recommendation. Finally, extensive experiments on real-world data demonstrate that NSR can achieve a superior serendipity by a 12% improvement in average while maintaining stable accuracy compared with state-of-the-art methods.\n          <\/jats:p>","DOI":"10.1145\/3396607","type":"journal-article","created":{"date-parts":[[2020,6,16]],"date-time":"2020-06-16T10:06:57Z","timestamp":1592302017000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["Neural Serendipity Recommendation"],"prefix":"10.1145","volume":"14","author":[{"given":"Yuanbo","family":"Xu","sequence":"first","affiliation":[{"name":"Jilin University, Changchun, Jilin, China"}]},{"given":"Yongjian","family":"Yang","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, Jilin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6112-2923","authenticated-orcid":false,"given":"En","family":"Wang","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, Jilin, China"}]},{"given":"Jiayu","family":"Han","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, Jilin, China"}]},{"given":"Fuzhen","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Key Lab of Intelligent Information Processing of Chinese Academy of Sciences and Beijing Advanced Innovation Center for Imaging Theory and Technology, China"}]},{"given":"Zhiwen","family":"Yu","sequence":"additional","affiliation":[{"name":"Northwestern Polytechnical University, Shanxi, China"}]},{"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[{"name":"Rutgers, The State University of New Jersey, Newark, NJ"}]}],"member":"320","published-online":{"date-parts":[[2020,6,16]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Recommender Systems Handbook","author":"Adomavicius Gediminas"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.03.012"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2566622"},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the 29th International Conference on Machine Learning (ICML'12)","author":"Chen Minmin","year":"2012"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052585"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1561\/9781601988157"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.03.023"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2843948"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the Advances in Neural Information Processing Systems. 2672--2680","author":"Goodfellow Ian","year":"2014"},{"key":"e_1_2_1_10_1","volume-title":"Deep Learning","author":"Goodfellow Ian"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.02.013"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911489"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209981"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498253"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_2_1_17_1","first-page":"2","article-title":"Diversity, serendipity, novelty, and coverage: A survey and empirical analysis of beyond-accuracy objectives in recommender systems","volume":"7","author":"Kaminskas Marius","year":"2016","journal-title":"ACM Transactions on Interactive Intelligent Systems"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.5220\/0005879802510256"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.08.014"},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the International Conference on Web Information Systems and Technologies. 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