{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:55:54Z","timestamp":1773248154180,"version":"3.50.1"},"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":[[2019,8]]},"abstract":"<jats:p>Analyzing large-scale evolving graphs are crucial for understanding the dynamic and evolutionary nature of social networks. Most existing works focus on discovering repeated and consistent temporal patterns, however, such patterns cannot fully explain the complexity observed in dynamic networks. For example, in recommendation scenarios, users sometimes purchase products on a whim during a window shopping.Thus, in this paper, we design and implement a novel framework called BurstGraph which can capture both recurrent and consistent patterns, and especially unexpected bursty network changes. The performance of the proposed algorithm is demonstrated on both a simulated dataset and a world-leading E-Commerce company dataset, showing that they are able to discriminate recurrent events from extremely bursty events in terms of action propensity.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/613","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"4412-4418","source":"Crossref","is-referenced-by-count":18,"title":["Large Scale Evolving Graphs with Burst Detection"],"prefix":"10.24963","author":[{"given":"Yifeng","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University"}]},{"given":"Xiangwei","family":"Wang","sequence":"additional","affiliation":[{"name":"DAMO Academy, Alibaba Group"}]},{"given":"Hongxia","family":"Yang","sequence":"additional","affiliation":[{"name":"DAMO Academy, Alibaba Group"}]},{"given":"Le","family":"Song","sequence":"additional","affiliation":[{"name":"Ant Financial"}]},{"given":"Jie","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:50:28Z","timestamp":1564285828000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/613"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/613","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}