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Gerhards, \u201cThe syslog protocol,\u201d RFC 5424, 2009. http:\/\/tools.ietf.org\/html\/rfc5424","DOI":"10.17487\/rfc5424"},{"key":"2","unstructured":"[2] CA Spectrum. http:\/\/www.ca.com\/us\/root-cause-analysis.aspx"},{"key":"3","unstructured":"[3] HP Software. http:\/\/www8.hp.com\/us\/en\/software\/enterprise-software.html"},{"key":"4","unstructured":"[4] IBM Tivoli. http:\/\/www-01.ibm.com\/software\/tivoli"},{"key":"5","unstructured":"[5] Logentries. http:\/\/ogentries.com"},{"key":"6","unstructured":"[6] Splunk. http:\/\/www.splunk.com"},{"key":"7","unstructured":"[7] USENIX The computer failure data repository (CFDR). http:\/\/www.usenix.org\/cfdr-data"},{"key":"8","unstructured":"[8] Cisco 7200 Series Routers Processor Memory Parity Errors Support Page. http:\/\/www.cisco.com\/c\/en\/us\/support\/docs\/routers\/7200-series-routers\/6345-crashes-pmpe.html"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] P. Bahl, R. Chandra, A. Greenberg, S. Kandula, D.A. Maltz, and M. Zhang, \u201cTowards highly reliable enterprise network services via inference of multi-level dependencies,\u201d Proc. SIGCOMM &apos;07, pp.13-24, New York, USA, 2007. 10.1145\/1282427.1282383","DOI":"10.1145\/1282427.1282383"},{"key":"10","unstructured":"[10] X. Chen, M. Zhang, Z.M. Mao, and P. Bahl, \u201cAutomating network application dependency discovery: experiences, limitations, and new solutions,\u201d Proc. OSDI &apos;08, pp.117-130, San Diego, USA, 2008."},{"key":"11","unstructured":"[11] K. Crammer, O. Dekel, J. Keshet, S.S.-Shwartz, and Y. Singer, \u201cOnline passive-aggressive algorithms,\u201d J. Mach. Learn., vol.7, pp.551-585, 2006."},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] C. Cortes and V. Vapnik, \u201cSupport-vector networks,\u201d Mach. Learn., vol.20, no.3, pp.273-297, 1995. 10.1007\/bf00994018","DOI":"10.1007\/BF00994018"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Q. Fu, J.-G. Lou, Y. Wang, and J. Li, \u201cExecution anomaly detection in distributed systems through unstructured log analysis,\u201d Proc. ICDM &apos;09, pp.149-158, Miami, USA, 2009. 10.1109\/icdm.2009.60","DOI":"10.1109\/ICDM.2009.60"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] J.M.N. Gonzalez, J.A. Jimenez, J.C.D. Lopez, and H.A. Parada G., \u201cRoot cause analysis of network failures using machine learning and summarization techniques,\u201d IEEE Commun. Mag., vol.55, no.9, pp.126-131, 2017. 10.1109\/mcom.2017.1700066","DOI":"10.1109\/MCOM.2017.1700066"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] S. Kandula, R. Chandra, and D. Katabi, \u201cWhat&apos;s going on? Learning communication rules in edge networks,\u201d Proc. SIGCOMM &apos;08, pp.87-98, Seattle, USA, 2008. 10.1145\/1402958.1402970","DOI":"10.1145\/1402958.1402970"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] S. Kandura, R. Mahajan, P. Verkaik, S. Agarwal, J. Padhye, and P. Bahl, \u201cDetailed diagnosis in enterprise networks,\u201d Proc. SIGCOMM &apos;09, pp.243-254, Barcelona, Spain, 2009. 10.1145\/1592568.1592597","DOI":"10.1145\/1592568.1592597"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] T. Kimura, A. Watanabe, T. Toyono, and K. Ishibashi, \u201cProactive failure detection learning generation patterns of large-scale network logs,\u201d Proc. CNSM &apos;15, pp.8-14, Barcelona, Spain, 2015. 10.1109\/cnsm.2015.7367332","DOI":"10.1109\/CNSM.2015.7367332"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] T. Kimura, K. Ishibashi, T. Mori, H. Sawada, T. Toyono, K. Nishimatsu, A. Watanabe, A. Shimoda, and K. Shiomoto, \u201cNetwork event extraction from log data with nonnegative tensor factorization,\u201d IEICE Trans. Commun., vol.E100-B, no.10, pp.1865-1878, Oct. 2017. 10.1587\/transcom.2016ebp3430","DOI":"10.1587\/transcom.2016EBP3430"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] J. Kleinberg, \u201cBursty and hierarchical structure in streams,\u201d Proc. KDD &apos;02, pp.91-101, Edmonton, Canada, 2002. 10.1145\/775060.775061","DOI":"10.1145\/775060.775061"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] S. Kobayashi, K. Fukuda, and H. Esaki, \u201cMining causes of network events in log data with causal inference,\u201d Proc. of IM &apos;17, pp.45-53, Lisbon, Portugal, 2017. 10.23919\/inm.2017.7987263","DOI":"10.23919\/INM.2017.7987263"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] T. Li, F. Liang, S. Ma, and W. Pengo, \u201cAn integrated framework on mining logs files for computing system management,\u201d KDD &apos;05, pp.776-781, Chicago, USA, 2005. 10.1145\/1081870.1081972","DOI":"10.1145\/1081870.1081972"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] C. Lim, N. Singh, and S. Yajnik, \u201cA log mining approach to failure analysis of enterprise telephony systems,\u201d Proc. DSN &apos;08, pp.398-403, Anchorage, USA, 2008. 10.1109\/dsn.2008.4630109","DOI":"10.1109\/DSN.2008.4630109"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] A. Mahimkar, J. Yates, Y. Zhang, A. Shaikh, J. Wang, Z. Ge, and C.T. Ee, \u201cTroubleshooting chronic conditions in large IP networks,\u201d Proc. CoNEXT &apos;08, pp.2:1-2:12, Madrid, Spain, 2008. 10.1145\/1544012.1544014","DOI":"10.1145\/1544012.1544014"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[24] M. Mizutani, \u201cIncremental mining of system log format,\u201d Proc. SCC &apos;13, pp.595-602, Santa Clara, USA, 2013. 10.1109\/scc.2013.73","DOI":"10.1109\/SCC.2013.73"},{"key":"25","unstructured":"[25] R. Potharaju, N. Jain, and C.N.-Rotaru, \u201cJuggling the jigsaw: Towards automated problem inference from network trouble tickets,\u201d NSDI &apos;13, pp.127-142, Lombard, USA, 2013."},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] T. Qiu, Z. Ge, D. Pei, J. Wang, and J. Xu, \u201cWhat happened in my network? Mining network events from router syslogs,\u201d Proc. IMC &apos;10, pp.472-484, Melbourne, Australia, 2010. 10.1145\/1879141.1879202","DOI":"10.1145\/1879141.1879202"},{"key":"27","doi-asserted-by":"publisher","unstructured":"[27] W.M. Rand, \u201cObjective criteria for the evaluation of clustering methods,\u201d J. Am. Stat. Assoc., vol.66, no.336, pp.846-850, 1971. 10.1080\/01621459.1971.10482356","DOI":"10.1080\/01621459.1971.10482356"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] T. Reidemeister, M. Jiang, and P.A.S. Ward, \u201cMining unstructured log files for recurrent fault diagnosis,\u201d Proc. IM (Mini Conf.), pp.377-384, Dublin, Ireland, 2011. 10.1109\/inm.2011.5990536","DOI":"10.1109\/INM.2011.5990536"},{"key":"29","doi-asserted-by":"crossref","unstructured":"[29] R. Sipos, D. Fradkin, F. Moerchen, and Z. Wang, \u201cLog-based predictive maintenance,\u201d Proc. SIGKDD &apos;14, pp.1867-1876, New York, USA, 2014. 10.1145\/2623330.2623340","DOI":"10.1145\/2623330.2623340"},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] M. Tariq, A. Zeitoun, V. Valancius, N. Feamster, and M. Ammar, \u201cAnswering what-if deployment and configuration questions with wise,\u201d Proc. SIGCOMM &apos;08, pp.99-110, Seattle, USA, 2008. 10.1145\/1402958.1402971","DOI":"10.1145\/1402958.1402971"},{"key":"31","doi-asserted-by":"crossref","unstructured":"[31] T. Wang, M. Srivatsa, D. Agrawal, and L. Liu, \u201cLearning, indexing, and diagnosing network faults,\u201d Proc. SIGKDD &apos;09, pp.857-866, Paris, France, 2009. 10.1145\/1557019.1557113","DOI":"10.1145\/1557019.1557113"},{"key":"32","doi-asserted-by":"crossref","unstructured":"[32] T. Wang, M. Srivatsa, D. Agrawal, and L. Liu, \u201cSpatio-temporal patterns in network events,\u201d Proc. CoNEXT &apos;10, pp.3:1-3:12, Philadelphia, USA, 2010. 10.1145\/1921168.1921172","DOI":"10.1145\/1921168.1921172"},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] A. Watanabe, K. Ishibashi, T. Toyono, K. Watanabe, T. Kimura, Y. Matsuo, K. Shiomoto, and R. Kawahara, \u201cWorkflow extraction for service operation using multiple unstructured trouble tickets,\u201d IEICE Trans. Inf. &amp; Syst., vol.E101-D, no.4, pp.1030-1041, April 2018. 10.1587\/transinf.2017dap0014","DOI":"10.1587\/transinf.2017DAP0014"},{"key":"34","doi-asserted-by":"crossref","unstructured":"[34] R. Vaarandi, \u201cA data clustering algorithm for mining patterns from event logs,\u201d Proc. IPOM, pp.119-126, Kansas City, USA, 2003. 10.1109\/ipom.2003.1251233","DOI":"10.1109\/IPOM.2003.1251233"},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] R. Vaarandi and K. Podi\u0146\u0161, \u201cNetwork IDS alert classification with frequent itemset mining and data clustering,\u201d Proc. CNSM &apos;10, pp.451-456, Niagara Falls, Canada, 2010. 10.1109\/cnsm.2010.5691262","DOI":"10.1109\/CNSM.2010.5691262"},{"key":"36","unstructured":"[36] W. Xu, L. Huang, A. Fox, D. Patterson, and M.I. Jordan, \u201cMining console logs for large-scale system problem detection,\u201d Proc. SysML &apos;08, p.4, San Diego, USA, 2008."},{"key":"37","doi-asserted-by":"crossref","unstructured":"[37] W. Xu, L. Huang, A. Fox, D. Patterson, and M.I. Jordan, \u201cDetecting large-scale system problems by mining console logs,\u201d Proc. SOSP &apos;09, pp.117-132, Big Sky, USA, 2009. 10.1145\/1629575.1629587","DOI":"10.1145\/1629575.1629587"},{"key":"38","doi-asserted-by":"crossref","unstructured":"[38] W. Xu, L. Huang, A. Fox, D. Patterson, and M.I. Jordan, \u201cOnline system problem detection by mining patterns of console logs,\u201d Proc. ICDM &apos;09, pp.588-597, Miami, USA, 2009. 10.1109\/icdm.2009.19","DOI":"10.1109\/ICDM.2009.19"},{"key":"39","doi-asserted-by":"crossref","unstructured":"[39] K. Yamanishi and M. Maruyama, \u201cDynamic syslog mining for network failure monitoring,\u201d Proc. SIGKDD &apos;05, pp.499-508, Chicago, USA, 2005. 10.1145\/1081870.1081927","DOI":"10.1145\/1081870.1081927"},{"key":"40","doi-asserted-by":"publisher","unstructured":"[40] H. Yan, L. Breslau, Z. Ge, D. Massey, D. Pei, and J. Yates, \u201cG-RCA: A generic root cause analysis platform for service quality management in large IP networks,\u201d IEEE\/ACM Trans. Netw., vol.20, no.6, pp.1734-1747, 2012. 10.1109\/tnet.2012.2188837","DOI":"10.1109\/TNET.2012.2188837"},{"key":"41","doi-asserted-by":"crossref","unstructured":"[41] K. Zhang, J. Xu, M.R. Min, G. Jiang, K. Pelechrinis, and H. Zhang, \u201cAutomated IT system failure prediction: A deep learning approach,\u201d Proc. Big Data, pp.1291-1300, Washington, USA, 2016. 10.1109\/bigdata.2016.7840733","DOI":"10.1109\/BigData.2016.7840733"},{"key":"42","doi-asserted-by":"crossref","unstructured":"[42] Z. Zheng, Z. Lan, B.H. Park, and A. Geist, \u201cSystem log pre-processing to improve failure prediction,\u201d Proc. DSN &apos;09, pp.572-577, Lisbon, Portugal, 2009. 10.1109\/dsn.2009.5270289","DOI":"10.1109\/DSN.2009.5270289"},{"key":"43","doi-asserted-by":"crossref","unstructured":"[43] B. Zhong, Y. Wu, J. Song, A.K. Singh, H. Cam, J. Han, and X. Yan, \u201cTowards scalable critical alert mining,\u201d Proc. SIGKDD &apos;14, pp.1057-1066, New York, USA, 2014. 10.1145\/2623330.2623729","DOI":"10.1145\/2623330.2623729"},{"key":"44","doi-asserted-by":"publisher","unstructured":"[44] K.Q. Zhu, K. Fisher, and D. Walker, \u201cIncremental learning of system log formats,\u201d ACM SIGOPS Oper. Syst. 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