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Shimin Tao
Researcher at Huawei
Publications - 57
Citations - 423
Shimin Tao is an academic researcher from Huawei. The author has contributed to research in topics: Computer science & Machine translation. The author has an hindex of 6, co-authored 21 publications receiving 162 citations. Previous affiliations of Shimin Tao include Baidu.
Papers
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Proceedings ArticleDOI
LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs
Weibin Meng,Ying Liu,Yichen Zhu,Shenglin Zhang,Dan Pei,Yuqing Liu,Yihao Chen,Ruizhi Zhang,Shimin Tao,Pei Sun,Rong Zhou +10 more
TL;DR: 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 has not been done by any previous work.
Journal ArticleDOI
FUNNEL: Assessing Software Changes in Web-Based Services
Shenglin Zhang,Ying Liu,Dan Pei,Chen Yu,Qu Xianping,Shimin Tao,Zang Zhi,Xiaowei Jing,Mei Feng +8 more
TL;DR: An automated tool for rapid and robust impact assessment of software changes in large Internet-based services, FUNNEL, which achieves a 98.21 percent precision, high robustness, fast detection speed, and shows its capability in detecting unexpected behavior changes.
Proceedings ArticleDOI
Rapid and robust impact assessment of software changes in large internet-based services
TL;DR: An automated tool for rapid and robust impact assessment of software changes in large Internet-based services, FUNNEL, which achieves a 98.21% precision, high robustness, fast detection speed, and shows its capability in detecting unexpected performance changes.
Proceedings ArticleDOI
LogParse: Making Log Parsing Adaptive through Word Classification
Weibin Meng,Ying Liu,Federico Zaiter,Shenglin Zhang,Yihao Chen,Yuzhe Zhang,Yichen Zhu,En Wang,Ruizhi Zhang,Shimin Tao,Dian Yang,Rong Zhou,Dan Pei +12 more
TL;DR: This work proposes LogParse, an adaptive log parsing framework, to support intra-service and cross-service incremental template learning and update, which turns the template generation problem into a word classification problem and learns the features of template words and variable words.
Posted Content
Summarizing Unstructured Logs in Online Services.
Weibin Meng,Federico Zaiter,Yuheng Huang,Ying Liu,Shenglin Zhang,Yuzhe Zhang,Yichen Zhu,Tianke Zhang,En Wang,Zuomin Ren,Feng Wang,Shimin Tao,Dan Pei +12 more
TL;DR: This work proposes LogSummary, an automatic, unsupervised end-to-end log summarization framework for online services that obtains the summarized triples of important logs for a given log sequence with a new triple ranking approach using the global knowledge learned from all logs.