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Software and System logs record runtime information about processes executing within a system.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Lof: Identifying density-based local outliers
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, and Jörg Sander · 2000
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Estimating the support of a high-dimensional distribution
Bernhard Schölkopf, John C. Platt, John C. Shawe-Taylor, Alex J. Smola, and Robert C. Williamson · 2001
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Using tf-idf to determine word relevance in document queries
Juan Ramos et al · 2003
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An automated approach for abstracting execution logs to execution events
Zhen Ming Jiang, Ahmed E Hassan, Gilbert Hamann, and Parminder Flora · 2008
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Abstracting execution logs to execution events for enterprise applications (short paper)
Zhen Ming Jiang, Ahmed E. Hassan, Parminder Flora, and Gilbert Hamann · 2008
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Clustering event logs using iterative partitioning
Adetokunbo AO Makanju, A Nur Zincir-Heywood, and Evangelos E Milios · 2009
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Clustering event logs using iterative partitioning
Adetokunbo A.O. Makanju, A. Nur Zincir-Heywood, and Evangelos E. Milios · 2009
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Web-scale k-means clustering
D. Sculley · 2010
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Experience report: Anomaly detection of cloud application operations using log and cloud metric correlation analysis
Mostafa Farshchi, Jean-Guy Schneider, Ingo Weber, and John Grundy · 2015
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Experience report: System log analysis for anomaly detection
Shilin He, Jieming Zhu, Pinjia He, and Michael R. Lyu · 2016
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Experience report: System log analysis for anomaly detection
Shilin He, Jieming Zhu, Pinjia He, and Michael R. Lyu · 2016
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Drain: An online log parsing approach with fixed depth tree
Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R Lyu · 2017
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Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Dbscan revisited, revisited: Why and how you should (still) use dbscan
Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, and Xiaowei Xu · 2017
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Drain: An online log parsing approach with fixed depth tree
Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R. Lyu · 2017
Experience report: Deep learning-based system log analysis for anomaly detection, 2021
Zhuangbin Chen, Jinyang Liu, Wenwei Gu, Yuxin Su, and Michael R. Lyu · 2021
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Merlion: A machine learning library for time series
Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K C Krithika, Sukumar Maddineni, Daeki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven Hoi, and Huan Wang · 2021
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A survey on log research of aiops: Methods and trends
Jiang Zhaoxue, Li Tong, Zhang Zhenguo, Ge Jingguo, You Junling, and Li Liangxiong · 2021
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A survey on automated log analysis for reliability engineering
Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, and Michael R. Lyu · 2021
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A survey of aiops methods for failure management
Paolo Notaro, Jorge Cardoso, and Michael Gerndt · 2021
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Deeplog: Anomaly detection and diagnosis from system logs through deep learning
Min Du, Feifei Li, Guineng Zheng, and Vivek Srikumar · 2017
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Detecting anomaly in big data system logs using convolutional neural network
Siyang Lu, Xiang Wei, Yandong Li, and Liqiang Wang · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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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, and Rong Zhou · 2019
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Robust log-based anomaly detection on unstable log data
Xu Zhang, Yong Xu, Qingwei Lin, Bo Qiao, Hongyu Zhang, Yingnong Dang, Chunyu Xie, Xinsheng Yang, Qian Cheng, Ze Li, Junjie Chen, Xiaoting He, Randolph Yao, Jian-Guang Lou, Murali Chintalapati, Furao Shen, and Dongmei Zhang · 2019
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Self-attentive classification-based anomaly detection in unstructured logs
Sasho Nedelkoski, Jasmin Bogatinovski, Alexander Acker, Jorge Cardoso, and Odej Kao · 2020
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Unsupervised cross-system log anomaly detection via domain adaptation
Xiao Han and Shuhan Yuan · 2021
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An empirical investigation of practical log anomaly detection for online service systems
Nengwen Zhao, Honglin Wang, Zeyan Li, Xiao Peng, Gang Wang, Zhu Pan, Yong Wu, Zhen Feng, Xidao Wen, Wenchi Zhang, Kaixin Sui, and Dan Pei · 2021
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Unilog: Deploy one model and specialize it for all log analysis tasks
Yichen Zhu, Weibin Meng, Ying Liu, Shenglin Zhang, Tao Han, Shimin Tao, and Dan Pei · 2021
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Lanobert : System log anomaly detection based on BERT masked language model
Yukyung Lee, Jina Kim, and Pilsung Kang · 2021
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A survey on log research of aiops: Methods and trends
Jiang Zhaoxue, Li Tong, Zhang Zhenguo, Ge Jingguo, You Junling, and Li Liangxiong · 2022
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Log-based anomaly detection with deep learning: How far are we?
Van-Hoang Le and Hongyu Zhang · 2022
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Anomaly detection and failure root cause analysis in (micro) service-based cloud applications: A survey
Jacopo Soldani and Antonio Brogi · 2022
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Log Management Global Market Report
The Business Research Company · 2023
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