Y. Liu, X. Zhang, S. He, H. Zhang, L. Li, Y. Kang, Y. Xu, M. Ma, Q. Lin, Y. Dang, S. Rajmohan, and D. Zhang, “Uniparser: A unified log parser for heterogeneous log data,” in Proceedings of the ACM Web Conference 2022 , ser. WWW ’22. Association for Computing Machinery, 2022, p. 1893–1901
1901
Earlier work this paper cites.
M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander, “Lof: identifying density-based local outliers,” in ACM sigmod record , vol. 29, no. 2. ACM, 2000, pp. 93–104
2000
Earlier work this paper cites.
B. Schölkopf, J. C. Platt, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson, “Estimating the support of a high-dimensional distribution,” Neural Computation , vol. 13, no. 7, pp. 1443–1471, 2001
2001
Earlier work this paper cites.
K. Hätönen, J. Boulicaut, M. Klemettinen, M. Miettinen, and C. Masson, “Comprehensive log compression with frequent patterns,” in Data Warehousing and Knowledge Discovery, 5th International Conference, DaWaK 2003, Prague, Czech Republic, September 3-5,2003, Proceedings , 2003, pp. 360–370
2003
Earlier work this paper cites.
R. Vaarandi, “A data clustering algorithm for mining patterns from event logs,” in IP Operations & Management, 2003.(IPOM 2003). 3rd IEEE Workshop on . IEEE, 2003, pp. 119–126
2003
Earlier work this paper cites.
M. Chen, A. X. Zheng, J. Lloyd, M. I. Jordan, and E. Brewer, “Failure diagnosis using decision trees,” in International Conference on Autonomic Computing (ICAC) . IEEE, 2004, pp. 36–43
2004
Earlier work this paper cites.
B. Rácz and A. Lukács, “High density compression of log files,” in 2004 Data Compression Conference (DCC 2004), 23-25 March 2004, Snowbird, UT, USA , 2004, p. 557
2004
Earlier work this paper cites.
Y. Liang, Y. Zhang, A. Sivasubramaniam, R. K. Sahoo, J. Moreira, and M. Gupta, “Filtering failure logs for a bluegene/l prototype,” in 2005 International Conference on Dependable Systems and Networks (DSN’05) . IEEE, 2005, pp. 476–485
2005
Earlier work this paper cites.
Y. Liang, Y. Zhang, H. Xiong, and R. Sahoo, “Failure prediction in ibm bluegene/l event logs,” in the 7th IEEE International Conference on Data Mining (ICDM) . IEEE, 2007, pp. 583–588
2007
Earlier work this paper cites.
A. Oliner and J. Stearley, “What supercomputers say: A study of five system logs,” in DSN , 2007
2007
Earlier work this paper cites.
S. Deorowicz and S. Grabowski, “Sub-atomic field processing for improved web log compression,” in Modern Problems of Radio Engineering, Telecommunications and Computer Science, 2008 Proceedings of International Conference on . IEEE, 2008, pp. 551–556
2008
Earlier work this paper cites.
Z. M. Jiang, A. E. Hassan, P. Flora, and G. Hamann, “Abstracting execution logs to execution events for enterprise applications (short paper),” in 2008 The Eighth International Conference on Quality Software . IEEE, 2008, pp. 181–186
2008
Earlier work this paper cites.
F. T. Liu, K. M. Ting, and Z.-H. Zhou, “Isolation forest,” in the 8th IEEE International Conference on Data Mining (ICDM) . IEEE, 2008, pp. 413–422
2008
Earlier work this paper cites.
C. Manning, P. Raghavan, and H. Schutze, Introduction to Information Retrieval . Cambridge University Press, 2008
2008
Earlier work this paper cites.
Q. Fu, J. Lou, Y. Wang, and J. Li, “Execution anomaly detection in distributed systems through unstructured log analysis,” in ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009 , 2009, pp. 149–158
2009
Earlier work this paper cites.
——, “Execution anomaly detection in distributed systems through unstructured log analysis,” in ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009 , 2009, pp. 149–158
2009
Earlier work this paper cites.
A. Makanju, A. N. Zincir-Heywood, and E. E. Milios, “Clustering event logs using iterative partitioning,” in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009 , 2009, pp. 1255–1264
2009
Earlier work this paper cites.
W. Xu, L. Huang, A. Fox, D. A. Patterson, and M. I. Jordan, “Detecting large-scale system problems by mining console logs,” in SOSP , 2009, pp. 117–132
2009
Earlier work this paper cites.
P. Bodik, M. Goldszmidt, A. Fox, D. B. Woodard, and H. Andersen, “Fingerprinting the datacenter: automated classification of performance crises,” in Proceedings of the 5th European Conference on Computer Systems (EuroSys) . ACM, 2010, pp. 111–124
2010
Earlier work this paper cites.
J.-G. Lou, Q. Fu, S. Yang, Y. Xu, and J. Li, “Mining invariants from console logs for system problem detection.” in USENIX Annual Technical Conference , 2010, pp. 1–14
2010
Earlier work this paper cites.
M. Nagappan and M. A. Vouk, “Abstracting log lines to log event types for mining software system logs,” in 2010 7th IEEE Working Conference on Mining Software Repositories (MSR) , 2010, pp. 114–117
2010
Earlier work this paper cites.
——, “Detecting large-scale system problems by mining console logs,” in Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel , 2010, pp. 37–46
2010
Earlier work this paper cites.
I. Beschastnikh, Y. Brun, S. Schneider, M. Sloan, and M. D. Ernst, “Leveraging existing instrumentation to automatically infer invariant-constrained models,” in Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering (FSE) . ACM, 2011, pp. 267–277
2011
Earlier work this paper cites.
L. Tang, T. Li, and C. Perng, “Logsig: generating system events from raw textual logs,” in Proceedings of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24-28, 2011 , 2011, pp. 785–794
2011
Earlier work this paper cites.
G. Lee, J. J. Lin, C. Liu, A. Lorek, and D. V. Ryaboy, “The unified logging infrastructure for data analytics at twitter,” PVLDB , vol. 5, no. 12, pp. 1771–1780, 2012. [Online]. Available: http://vldb.org/pvldb/vol5/p1771_georgelee_vldb2012.pdf
2012
Earlier work this paper cites.
D. Yuan, S. Park, and Y. Zhou, “Characterizing logging practices in open-source software,” in Proceedings of the 34th International Conference on Software Engineering . IEEE Press, 2012, pp. 102–112
2012
Earlier work this paper cites.
R. Christensen and F. Li, “Adaptive log compression for massive log data,” in Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD) , 2013, pp. 1283–1284
2013
Earlier work this paper cites.