{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T09:30:11Z","timestamp":1777714211644,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":12,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,23]]},"DOI":"10.1145\/3394486.3406711","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T23:03:53Z","timestamp":1597964633000},"page":"3519-3520","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["In Search for a Cure"],"prefix":"10.1145","author":[{"given":"Iris","family":"Shen","sequence":"first","affiliation":[{"name":"Microsoft, Redmond, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Le","family":"Zhang","sequence":"additional","affiliation":[{"name":"Microsoft, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxun","family":"Lian","sequence":"additional","affiliation":[{"name":"Microsoft, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chieh-Han","family":"Wu","sequence":"additional","affiliation":[{"name":"Microsoft, Redmond, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel Gonzalez","family":"Fierro","sequence":"additional","affiliation":[{"name":"Microsoft.com, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Argyriou","sequence":"additional","affiliation":[{"name":"Microsoft, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Wu","sequence":"additional","affiliation":[{"name":"Microsoft, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2020. CORD-19 Data set. https:\/\/pages.semanticscholar.org\/coronavirus-research  2020. CORD-19 Data set. https:\/\/pages.semanticscholar.org\/coronavirus-research"},{"key":"e_1_3_2_1_2_1","unstructured":"2020. Microsoft Academic Graph. https:\/\/docs.microsoft.com\/enus\/academic-services\/graph\/.  2020. Microsoft Academic Graph. https:\/\/docs.microsoft.com\/enus\/academic-services\/graph\/."},{"key":"e_1_3_2_1_3_1","unstructured":"2020. Microsoft Academic Graph Research on COVID-19. https:\/\/github.com\/microsoft\/mag-covid19-research-examples  2020. Microsoft Academic Graph Research on COVID-19. https:\/\/github.com\/microsoft\/mag-covid19-research-examples"},{"key":"e_1_3_2_1_4_1","unstructured":"2020. Understanding Documents By Using Semantics. https:\/\/www.microsoft.com\/en-us\/research\/project\/academic\/articles\/understanding-documents-by-using-semantics\/  2020. Understanding Documents By Using Semantics. https:\/\/www.microsoft.com\/en-us\/research\/project\/academic\/articles\/understanding-documents-by-using-semantics\/"},{"key":"e_1_3_2_1_5_1","volume-title":"Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. In Companion Proceedings of the Web Conference","author":"Argyriou Andreas","year":"2020","unstructured":"Andreas Argyriou , Miguel Gonz\u00e1lez-Fierro , and Le Zhang . 2020 . Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. In Companion Proceedings of the Web Conference 2020. 50--51. Andreas Argyriou, Miguel Gonz\u00e1lez-Fierro, and Le Zhang. 2020. Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems. In Companion Proceedings of the Web Conference 2020. 50--51."},{"key":"e_1_3_2_1_6_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in neural information processing systems. 1024--1034.  Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in neural information processing systems. 1024--1034."},{"key":"e_1_3_2_1_7_1","volume-title":"LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. arXiv preprint arXiv:2002.02126","author":"He Xiangnan","year":"2020","unstructured":"Xiangnan He , Kuan Deng , Xiang Wang , Yan Li , Yongdong Zhang , and MengWang. 2020. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. arXiv preprint arXiv:2002.02126 ( 2020 ). Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, and MengWang. 2020. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. arXiv preprint arXiv:2002.02126 (2020)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308560.3320095"},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of the 2018 world wide web conference. 1835--1844","author":"Zhang Fuzheng","year":"2018","unstructured":"HongweiWang, Fuzheng Zhang , Xing Xie , and Minyi Guo . 2018 . DKN: Deep knowledge-aware network for news recommendation . In Proceedings of the 2018 world wide web conference. 1835--1844 . HongweiWang, Fuzheng Zhang, Xing Xie, and Minyi Guo. 2018. DKN: Deep knowledge-aware network for news recommendation. In Proceedings of the 2018 world wide web conference. 1835--1844."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1162\/qss_a_00021"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2019.00045"}],"event":{"name":"KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event CA USA","acronym":"KDD '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3406711","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3406711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:30Z","timestamp":1750195890000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3406711"}},"subtitle":["Recommendation With Knowledge Graph on CORD-19"],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":12,"alternative-id":["10.1145\/3394486.3406711","10.1145\/3394486"],"URL":"https:\/\/doi.org\/10.1145\/3394486.3406711","relation":{},"subject":[],"published":{"date-parts":[[2020,8,20]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}