Eamonn J. Keogh Papers on DiSC'03 Mining Motifs in Massive Time Series Databases On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration Finding Surprising Patterns in a Time Series Database In Linear Time and Space Locally adaptive dimensionality reduction for indexing large time series databases Exact Indexing of Dynamic Time Warping Publications Note: Links lead to the DBLP on the Web. Eamonn J. Keogh 19 Eamonn J. Keogh, Harry Hochheiser , Ben Shneiderman : An Augmented Visual Query Mechanism for Finding Patterns in Time Series Data. FQAS 2002 : 240-250 18 Pranav Patel , Eamonn J. Keogh, Jessica Lin , Stefano Lonardi : Mining Motifs in Massive Time Series Databases. ICDM 2002 : 370-377 17 Eamonn J. Keogh, Shruti Kasetty : On the need for time series data mining benchmarks: a survey and empirical demonstration. KDD 2002 : 102-111 16 Eamonn J. Keogh, Stefano Lonardi , Bill Yuan-chi Chiu : Finding surprising patterns in a time series database in linear time and space. KDD 2002 : 550-556 15 Eamonn J. Keogh: Exact Indexing of Dynamic Time Warping. VLDB 2002 : 406-417 14 Eamonn J. Keogh, Michael J. Pazzani : Learning the Structure of Augmented Bayesian Classifiers. International Journal on Artificial Intelligence Tools 11 (4): 587-601 (2002) 13 Kaushik Chakrabarti , Eamonn J. Keogh, Sharad Mehrotra , Michael J. Pazzani : Locally adaptive dimensionality reduction for indexing large time series databases. TODS 27 (2): 188-228 (2002) 12 Eamonn J. Keogh, Selina Chu , David Hart , Michael J. Pazzani : An Online Algorithm for Segmenting Time Series. ICDM 2001 : 289-296 11 Eamonn J. Keogh, Selina Chu , Michael J. Pazzani : Ensemble-index: a new approach to indexing large databases. KDD 2001 : 117-125 10 Eamonn J. Keogh, Kaushik Chakrabarti , Sharad Mehrotra , Michael J. Pazzani : Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases. SIGMOD Conference 2001 9 Eamonn J. Keogh, Kaushik Chakrabarti , Michael J. Pazzani , Sharad Mehrotra : Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases. Knowledge and Information Systems 3 (3): 263-286 (2001) 8 Eamonn J. Keogh, Michael J. Pazzani : Scaling up dynamic time warping for datamining applications. KDD 2000 : 285-289 7 Eamonn J. Keogh, Michael J. Pazzani : A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases. PAKDD 2000 : 122-133 6 Eamonn J. Keogh, Michael J. Pazzani : Scaling up Dynamic Time Warping to Massive Dataset. PKDD 1999 : 1-11 5 Eamonn J. Keogh, Michael J. Pazzani : Relevance Feedback Retrieval of Time Series Data. SIGIR 1999 : 183-190 4 Eamonn J. Keogh, Michael J. Pazzani : An Indexing Scheme for Fast Similarity Search in Large Time Series Databases. SSDBM 1999 : 56-67 3 Eamonn J. Keogh, Michael J. Pazzani : An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback. KDD 1998 : 239-243 2 Eamonn J. Keogh: Fast Similarity Search in the Presence of Longitudinal Scaling in Time Series Databases. ICTAI 1997 : 578-584 1 Eamonn J. Keogh, Padhraic Smyth : A Probabilistic Approach to Fast Pattern Matching in Time Series Databases. KDD 1997 : 24-30 DiSC'03 © 2003 Association for Computing Machinery