Publications

Click here to download the bibtex version of the bibliography.


Author Year Title Journal/Book Volume Number Pages
Bagnall, A. & Janacek, G. 2014 A run length transformation for discriminating between auto regressive time series Journal of Classification 31 154--178
Bagnall, A.; Lines, J.; Hills, J. & Bostrom, A. 2015 Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles {IEEE} Transactions on Knowledge and Data Engineering 27 2522--2535
Batista, G.; Keogh, E.; Tataw, O. & deSouza, V. 2014 CID: an efficient complexity-invariant distance measure for time series Data Mining and Knowledge Discovery 28 3 634--669
Baydogan, M. & Runger, G. 2015 Time series representation and similarity based on local autopatterns Data Mining and Knowledge Discovery
Baydogan, M.; Runger, G. & Tuv, E. 2013 A Bag-of-Features Framework to Classify Time Series {IEEE} Transactions on Pattern Analysis and Machine Intelligence 25 11 2796--2802
Bostrom, A. & Bagnall, A. 2015 Binary Shapelet Transform for Multiclass Time Series Classification Proc.17th {DaWaK}
Corduas, M. & Piccolo, D. 2008 Time series clustering and classification by the autoregressive metric Computational Statistics and Data Analysis 52 4 1860--1872
Deng, H.; Runger, G.; Tuv, E. & Vladimir, M. 2013 A time series forest for classification and feature extraction Information Sciences 239 142--153
Ding, H.; Trajcevski, G.; Scheuermann, P.; Wang, X. & Keogh, E. 2008 Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures Proc. 34th VLDB
Fulcher, B. & Jones, N. 2014 Highly comparative feature-based time-series classification {IEEE} Transactions on Knowledge and Data Engineering 26 12 3026--3037
G\'{o}recki, T. & \L{}uczak, M. 2013 Using derivatives in time series classification Data Mining and Knowledge Discovery 26 2 310--331
G\'{o}recki, T. & \L{}uczak, M. 2014 Non-isometric transforms in time series classification using DTW Knowledge-Based Systems 61 98--108
Grabocka, J. & Schmidt-Thieme, L. 2014 Invariant time-series factorization Data Mining and Knowledge Discovery 28 5 1455--1479
Grabocka, J.; Schilling, N.; Wistuba, M. & Schmidt-Thieme, L. 2014 Learning Time-Series Shapelets Proc. 20th {SIGKDD}
Hills, J.; Lines, J.; Baranauskas, E.; Mapp, J. & Bagnall, A. 2014 Classification of time series by shapelet transformation Data Mining and Knowledge Discovery 28 4 851--881
Jeong, Y.; Jeong, M. & Omitaomu, O. 2011 Weighted dynamic time warping for time series classification Pattern Recognition 44 2231--2240
Kate, R. 2015 Using dynamic time warping distances as features for improved time series classification Data Mining and Knowledge Discovery
Kate, R. 2015 Using dynamic time warping distances as features for improved time series classification Data Mining and Knowledge Discovery
Keogh, E. & Pazzani, M. 2001 Derivative dynamic time warping Proc. 1st {SDM}
Lin, J.; Keogh, E.; Li, W. & Lonardi, S. 2007 Experiencing SAX: A novel symbolic representation of time series Data Mining and Knowledge Discovery 15 2 107--144
Lin, J.; Khade, R. & Li, Y. 2012 Rotation-invariant similarity in time series using bag-of-patterns representation Journal of Intelligent Information Systems 39 2 287-315
Lines, J. & Bagnall, A. 2015 Time Series Classification with Ensembles of Elastic Distance Measures Data Mining and Knowledge Discovery 29 565--592
Marteau, P. 2009 Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching {IEEE} Transactions on Pattern Analysis and Machine Intelligence 31 2 306--318
Mueen, A.; Keogh, E. & Young, N. 2011 Logical-Shapelets: An Expressive Primitive for Time Series Classification Proc. 17th {SIGKDD}
Rakthanmanon, T. & Keogh, E. 2013 Fast-Shapelets: A Fast Algorithm for Discovering Robust Time Series Shapelets Proc. 13th {SDM}
Ratanamahatana, C. & Keogh, E. 2005 Three Myths about Dynamic Time Warping Data Mining Proc. 5th SDM
Rath, T. & Manamatha, R. 2003 Word image matching using dynamic time warping Proc. Computer Vision and Pattern Recognition
Rodr\'{i}guez, J.; Alonso, C. & Maestro, J. 2005 Support Vector Machines of Interval-based Features for Time Series Classification Knowledge-Based Systems 18 171--178
Sch{\a}fer, P. 2015 The BOSS is concerned with time series classification in the presence of noise Data Mining and Knowledge Discovery 29 6 1505--1530
Senin, P. & Malinchik, S. 2013 SAX-VSM: Interpretable Time Series Classification Using SAX and Vector Space Model Proc. 13th {IEEE ICDM}
D. Silva, V. de Souza, G. Batista 2013 Time Series Classification Using Compression Distance of Recurrence Plots Proc. 13th {IEEE ICDM}
Stefan, A.; Athitsos, V. & Das, G. 2013 The Move-Split-Merge Metric for Time Series {IEEE} Transactions on Knowledge and Data Engineering 25 6 1425--1438
Wang, X.; Mueen, A.; Ding, H.; Trajcevski, G.; Scheuermann, P. & Keogh, E. 2013 Experimental comparison of representation methods and distance measures for time series data Data Mining and Knowledge Discovery 26 2 275--309
Ye, L. & Keogh, E. 2011 Time series shapelets: a novel technique that allows accurate, interpretable and fast classification Data Mining and Knowledge Discovery 22 2 149-182