{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T02:41:01Z","timestamp":1784342461888,"version":"3.55.0"},"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>Recording runtime status via logs is common for almost every computer system, and detecting anomalies in logs is crucial for timely identifying malfunctions of systems. However, manually detecting anomalies for logs is time-consuming, error-prone, and infeasible. Existing automatic log anomaly detection approaches, using indexes rather than semantics of log templates, tend to cause false alarms. In this work, we propose LogAnomaly, a framework to model unstructured a log stream as a natural language sequence. Empowered by template2vec, a novel, simple yet effective method to extract the semantic information hidden in log templates, LogAnomaly can detect both sequential and quantitive log anomalies simultaneously, which were not done by any previous work. Moreover, LogAnomaly can avoid the false alarms caused by the newly appearing log templates between periodic model retrainings. Our evaluation on two public production log datasets show that LogAnomaly outperforms existing log-based anomaly detection methods.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/658","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"4739-4745","source":"Crossref","is-referenced-by-count":554,"title":["LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs"],"prefix":"10.24963","author":[{"given":"Weibin","family":"Meng","sequence":"first","affiliation":[{"name":"Tsinghua University"},{"name":"Beijing National Research Center for Information Science and Technology (BNRist)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University"},{"name":"Beijing National Research Center for Information Science and Technology (BNRist)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichen","family":"Zhu","sequence":"additional","affiliation":[{"name":"University of Toronto"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shenglin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nankai University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Pei","sequence":"additional","affiliation":[{"name":"Tsinghua University"},{"name":"Beijing National Research Center for Information Science and Technology (BNRist)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Nankai University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihao","family":"Chen","sequence":"additional","affiliation":[{"name":"Tsinghua University"},{"name":"Beijing National Research Center for Information Science and Technology (BNRist)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruizhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huawei"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shimin","family":"Tao","sequence":"additional","affiliation":[{"name":"Huawei"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Sun","sequence":"additional","affiliation":[{"name":"Huawei"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Huawei"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"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":"2019-07-28T03:50:52Z","timestamp":1564285852000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/658"}},"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\/658","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}