CueT: Human-guided fast and accurate network alarm triage

Conference on Human Factors in Computing Systems - Proceedings

Volumn , Issue , 2011, Pages 157-166

  Amershi, Saleema ^a,b   Lee, Bongshin ^a   Kapoor, Ashish ^a   Mahajan, Ratul ^a   Christian, Blaine ^c  

^a MICROSOFT RESEARCH   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

^c MICROSOFT   (United States)

Author keywords

Interactive machine learning; Triage; Visualization

Indexed keywords

ALARM SYSTEMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

CURRENT PRACTICES; DYNAMIC ENVIRONMENTS; HEALTH INFORMATIONS; INTERACTIVE MACHINE LEARNING; LARGER NETWORKS; LEARNING TO LEARN; MACHINE LEARNING SYSTEMS; NOVEL VISUALIZATIONS; TRIAGE; USER STUDY;

VISUALIZATION;

EID: 79958125062     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1978942.1978966     Document Type: Conference Paper

References (18)

1. Appleby, K., Goldszmidt, G., and Steinder, M. Layered Event Correlation Engine for Multi-Domain Server Farms. Proc. INM 2001, IEEE (2001), 329-344.
2. Basu, S., Fisher, D., Drucker, S.M., and Lu, H. Assisting Users with Clustering Tasks by Combining Metric Learning and Classification. Proc. AAAI 2010.
3. Brugnosi, S., Bruno, G., Manione, R., Montariolo, E., Paschetta, E., and Sisto, L. An Expert System for Real Time Fault Diagnosis of the Italian Telecommunications Network. Proc. INM 1993, IEEE (1993), 617-628.
4. desJardins, M., MacGlashan, J., and Ferraioli, J. Interactive Visual Clustering. Proc. IUI 2007, ACM Press (2007), 361-364. (Pubitemid 47464036)
5. EMC Ionix, http://www.emc.com/products/family/ionix-family.htm
6. Fails, J.A. and Olsen, Jr., D.R. Interactive Machine Learning. Proc. IUI 2003, ACM Press (2003), 39-45.
7. Fisher, D., Maltz, D.A., Greenberg, A., Wang, X., Warncke, H., Robertson, G., and Czerwinski, M. Using Visualization to Support Network and Application Management in a Data Center. Proc. INM 2008, IEEE (2008), 1-6.
8. Fogarty, J., Tan, D., Kapoor, A., and Winder, S. CueFlik: Interactive Concept Learning in Image Search. Proc. CHI 2008, ACM Press (2008), 29-38.
9. Gardner, R.D. and Harle, D.A. Methods and Systems for Alarm Correlation. Proc. GLOBECOM 1996, IEEE (1996), 136-140.
10. HP OpenView, http://openview.hp.com
11. Jain, P., Kulis, B., Dhillon, I.S., and Grauman, K. Online Metric Learning and Fast Similarity Search. Proc. NIPS 2008, (2008), 761-768.
12. Jakobson, G. and Weissman, M.D. Alarm Correlation: Correlating multiple network alarms improves telecommunications network surveillance and fault management. IEEE Network 7, 6 (1993), 52-59.
13. Klementtinen, M., Mannila, H., and Toivonen, H. Rule Discovery in Telecommunication Alarm Data. J. Network and Systems Management 7, 4 (1999), 395-423. (Pubitemid 30530877)
14. Lakkaraju, K, Yurcik, W., and Lee, A.J. NVisionIP: Network Visualizations of System State for Security Situational Awareness. Proc. VizSEC/DMSEC 2004, ACM Press (2004), 65-72. (Pubitemid 40821174)
15. Liu, G., Mok, A.K., and Yang, E.J. Composite Events for Network Event Correlation. Proc. INM 1999, IEEE (1999), 247-260.
16. Spring, N., Mahajan, R., Wetherall, D., and Anderson, T. Measuring ISP Topologies with Rocketfuel. Proc. SIGCOMM 2002, ACM Press (2002), 133-145. (Pubitemid 43843780)
17. Steinder, M. and Sethi, A.S. A Survey of Fault Localization Techniques in Computer Networks. Science of Computer Programming 53, (2004), 165-194.
18. Yemini, S., Kliger, S., Mozes, E., Yemini, Y., and Ohsie, D. High Speed and Robust Event Correlation. IEEE Communications Magazine 34, 5 (1996), 82-90. (Pubitemid 126525244)