Visualizing frequent patterns in large multivariate time series

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7868, Issue , 2011, Pages

  Hao, M ^a   Marwah, M ^a   Janetzko, H ^b   Sharma, R ^a   Keim, D A ^b   Dayal, U ^a   Patnaik, D ^c   Ramakrishnan, N ^c  

^a HEWLETT PACKARD LABORATORIES   (United States)

^b UNIVERSITY OF KONSTANZ   (Germany)

^c VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Distortion; Merging; Motifs; Multivariate data; Recurring patterns; Time series

Indexed keywords

DATA CENTER COOLING; DEGREE OF DISTORTION; DISTORTION; ENCODING TECHNIQUES; FREQUENT PATTERNS; MOTIFS; MULTIVARIATE DATA; MULTIVARIATE TIME SERIES; PERFORMANCE METRICES; REAL WORLD DATA; RECURRING PATTERNS; SEQUENCE OF EVENTS; TEMPORAL DATA MINING; VISUAL ANALYTICS;

DATA VISUALIZATION; MERGING; OIL WELL PRODUCTION; OIL WELLS; TIME SERIES; VISUALIZATION;

TIME SERIES ANALYSIS;

EID: 79951902748     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.872169     Document Type: Conference Paper

References (17)

1. Agrawal, R, Srikant, R: Fast Algorithms for Mining Association Rules in Large Databases. VLDB 1994: 487-499
2. Buono, P., Aris, A., Plaisant, C., Khella, A., Shneiderman, B., Hochheiser, H. Schneiderman, B. Interactive Pattern Search in Time Series. Proceedings of Conference on Visualizaion and Data Analysis, VDA 2005, SPIE. CA.
3. C. Bash, C. Patel, R. Sharma, "Dynamic Thermal Management of Air Cooled Data Centers", IEEE Itherm06.
4. Bill Chiu, Eamonn Keogh, and Stefano Lonardi. Probabilistic discovery of time series motifs. In KDD '03: proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 493-498, New York, USA, 2003. ACM.
5. Chen, L., Ozsu, T. Oria, V. Symbolic Representation and Retrieval of Moving Object Trajectories. University of Waterloo. 2003.
6. Michael J. Moran and Howard N. Shapiro, Fundamentals of Engineering Thermodynamics, Wiley; 6 edition, 2007.
7. Hao, M. Dayal, U. Keim, D. A., Schreck, T., Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data. Proceedings: IEEE VGTC Symposium on Visualization, EuroVis 2007.
8. Lin, J., Keogh, E., Lonardi, E., and Patel, P., Finding motifs in time series. In Proceedings of the Second Workshop on Temporal Data Mining, 2002.
9. Lin, J., Keogh, E., Wei, L., and Lonardi, S. (2007) Experiencing SAX: a Novel Symbolic Representation of Time Series. DMKD Journal.
10. Patel, P., Koeogh, E, Lin, J., and Lonardi, S. Mining motifs in massive time series database. In ICDM'02: Proceedings of the 2002 IEEE International Conference on Data Mining (ICDN'02), page 370, Washington, DC. 2002.
11. J. Lin, E. Keogh, S. Lonardi, J. Lankford, D. Mystrom. VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Database. Proceedings of the 30th VLDB Conference, Canada, p#.1260, 2004.
12. McLachlan, P., Munnzner, T., Koutsofios, E. North S., LivePRAC: Interactive Visual Exploration of System Management Time-Series Data, CHI2008, 4/08 Florence, Italy.
13. Ordonez, P., des Jardins, M., Feltes, C. et. al. Visualizing Multivariate Time Series data to Detect Specific Medical Conditions. AMIA Annual Symposium Proceeding. 2008. MD.
14. Patnaik, D., Marwah, M. Sharma, R. Ramakrishnan, N. Sustainable Operation and Management of Data Center Chillers using Temporal Data Mining. In the proceedings of KDD'09, 6/09, France.
15. R. Sharma, C. Bash, C. Patel, "Dimensionless parameters for evaluation of thermal design and performance of large-scale data centers", 8th ASME/AIAA Joint Thermophysics and Heat Transfer Conf., St. Louis, MO, June 2002.
16. Sharma, R. et al. On building next generation data centers: Energy flow in the information technology stack, in Proceedings of Compute 2008.
17. R. Sharma et al., "Energy Flow in the Information Technology Stack", ACM Compute 2008.