{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T04:08:36Z","timestamp":1758946116368},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Infectious diseases have been recognized as major public health concerns for decades. Close contact  discovery is playing an indispensable role in preventing epidemic transmission. In this light, we study the continuous exposure search problem: Given a collection of moving objects and a collection of moving queries, we continuously discover all objects that have been directly and indirectly exposed to at least one query over a period of time. Our problem targets a variety of applications, including but not limited to disease control, epidemic pre-warning, information spreading, and co-movement mining. To answer this problem, we develop an exact group processing algorithm with optimization strategies. Further, we propose an approximate algorithm that substantially improves the efficiency without false dismissal. Extensive experiments offer insight into effectiveness and efficiency of our proposed algorithms.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/540","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"3891-3897","source":"Crossref","is-referenced-by-count":16,"title":["Towards Controlling the Transmission of Diseases: Continuous Exposure Discovery over Massive-Scale Moving Objects"],"prefix":"10.24963","author":[{"given":"Ke","family":"Li","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Lisi","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Shuo","family":"Shang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"},{"name":"Sichuan Artificial Intelligence Research Institute, Yibin, 644000, China"}]},{"given":"Haiyan","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China"}]},{"given":"Panos","family":"Kalnis","sequence":"additional","affiliation":[{"name":"King Abdullah University of Science and Technology"}]},{"given":"Bin","family":"Yao","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"}]}],"member":"10584","event":{"number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2022","name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","start":{"date-parts":[[2022,7,23]]},"theme":"Artificial Intelligence","location":"Vienna, Austria","end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:10:16Z","timestamp":1658128216000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/540"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/540","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}