{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T04:18:08Z","timestamp":1777436288928,"version":"3.51.4"},"reference-count":45,"publisher":"IEEE Comput. Soc","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1109\/icdm.2003.1250910","type":"proceedings-article","created":{"date-parts":[[2004,3,30]],"date-time":"2004-03-30T22:17:26Z","timestamp":1080685046000},"page":"115-122","source":"Crossref","is-referenced-by-count":106,"title":["Clustering of time series subsequences is meaningless: implications for previous and future research"],"prefix":"10.1109","author":[{"given":"E.","family":"Keogh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J.","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"W.","family":"Truppel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","article-title":"The Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns","author":"timmermann","year":"1998","journal-title":"FMG Discussion Papers dp0304 Financial Markets Group and ESRC"},{"key":"ref38","article-title":"Temporal Data Mining for the Discovery and Analysis of Ocean Climate Indices","author":"steinback","year":"0","journal-title":"2nd Workshop on Temporal Data Mining at the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1142\/S0218127400001092"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-35504-7_8"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/312129.312268"},{"key":"ref30","first-page":"200","article-title":"Extraction of Primitive Motion and Discovery of Association Rules from Human Motion","author":"mori","year":"2001","journal-title":"Proceedings of 10th IEEE International Workshop on Robot and Human Communication"},{"key":"ref37","article-title":"The Benefit of Information Reduction for Trading Strategies","author":"schittenkopf","year":"2000","journal-title":"Report Series for Adaptive Information Systems and Management in Economics and Management Science"},{"key":"ref36","article-title":"Parallel Algorithms for Mining Association Rules in Time Series Data","author":"sarker","year":"2002","journal-title":"TR-CS24–2002-1"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2002.1019212"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1089\/10665270050081360"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"},{"key":"ref40","article-title":"Temporal Pattern Recognition in Noisy Non-stationary Time Series Based on Quantization into Symbolic Streams: Lessons Learned from Financial Volatility Trading","author":"tino","year":"2000","journal-title":"Report Series for Adaptive Information Systems and Management in Economics and Management Science"},{"key":"ref11","first-page":"27","article-title":"Pattern Discovery from Stock Time Series Using Self-Organizing Maps","author":"fu","year":"0","journal-title":"Workshop Notes of KDD2001 Workshop on Temporal Data Mining"},{"key":"ref12","first-page":"487","article-title":"Mining the Stock Market: Which Measure is Best?","author":"gavrilov","year":"0","journal-title":"Proc 6th Int l Conf Knowledge Discovery and Data Mining"},{"key":"ref13","first-page":"359","article-title":"Clustering Data Streams","author":"mishra","year":"0","journal-title":"Proceedings of the 41st Annual Symposium on Foundations of Computer Science"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1023\/A:1012801612483","article-title":"On Clustering Validation Techniques","volume":"17","author":"halkidi","year":"2001","journal-title":"Journal of Intelligent Information Systems (JIIS)"},{"key":"ref15","first-page":"432","article-title":"Discovering Sequential Association Rules with Constraints and Time Lags in Multiple Sequences","author":"harms","year":"0","journal-title":"Proc Int l Symp Methodologies for Intelligent Systems"},{"key":"ref16","first-page":"9","article-title":"Data Mining in a Geospatial Decision Support system for Drought Risk Management","author":"harms","year":"0","journal-title":"proceedings of the Ist National Conference on Digital Government"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-45240-9_13"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1023\/A:1015516504614"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/846183.846195"},{"key":"ref28","article-title":"Finding motifs in time series","author":"lin","year":"2002","journal-title":"The 2nd Workshop on Temporal Data Mining at the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"},{"key":"ref4","first-page":"217","article-title":"When is Nearest Neighbor Meaningful?","author":"beyer","year":"0","journal-title":"7th International Conference on Database Theory"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/288627.288666"},{"key":"ref3","first-page":"39","article-title":"A New Approach to Analyzing Gene Expression Time Series Data","author":"bar-joseph","year":"0","journal-title":"proceedings of the 6th Annual Int'l Conference on Research in Computational Molecular Biology"},{"key":"ref6","article-title":"British Iris Society, Species Group Staff","year":"1997","journal-title":"A Guide to Species Irises Their Identification and Cultivation"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s100510050929"},{"key":"ref5","first-page":"91","article-title":"Refining Initial Points for K–Means Clustering","author":"bradley","year":"0","journal-title":"Proceedings of 15th International Conference on Machine Learning"},{"key":"ref8","first-page":"572","article-title":"Classification Rules + Time = Temporal Rules","author":"cotofrei","year":"0","journal-title":"In proceedings of the 2002 Int'l Conference on Computational Science"},{"key":"ref7","first-page":"24","article-title":"Statistical Temporal Rules","author":"cotofrei","year":"0","journal-title":"proceedings of the 15th Conference on Computational Statistics - Short Communications and Posters"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/170035.170072"},{"key":"ref9","first-page":"16","article-title":"Rule Discovery from Time Series","author":"das","year":"0","journal-title":"Proceedings of the 4th Int'l Conference on Knowledge Discovery and Data Mining"},{"key":"ref1","first-page":"420","article-title":"On the Surprising Behavior of Distance Metrics in High Dimensional Space","author":"aggarwal","year":"0","journal-title":"Proceedings of the 8th International Conference on Database Theory London"},{"key":"ref20","first-page":"469","article-title":"Distribution Discovery: Local Analysis of Temporal Rules","author":"jin","year":"0","journal-title":"Proceedings of the 6th Pacific-asia Conference on Knowledge Discovery and Data Mining"},{"key":"ref45","article-title":"Fault Detection by Mining Association Rules in House-keeping Data","author":"yairi","year":"0","journal-title":"Proceedings of the 6th International Symposium on Artificial Intelligence Robotics and Automation in Space"},{"key":"ref22","article-title":"Time-Series","author":"kendall","year":"1976","journal-title":"Charles Griffin & Company Ltd"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45675-9_12"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45884-0_24"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/B978-155860869-6\/50043-3"},{"key":"ref41","article-title":"A Hidden Constraint When Clustering Streaming Time Series","author":"keogh lin","year":"2003","journal-title":"Tech Rep UCR"},{"key":"ref23","author":"keogh","year":"2002","journal-title":"The UCR Time Series Data Mining Archive"},{"key":"ref44","article-title":"HotBits: Genuine Random Numbers Generated by Radioactive Decay","author":"walker","year":"2001"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/775047.775062"},{"key":"ref43","first-page":"464","article-title":"Combining the Kohonen Self-Organizing Map and K-Means for On-line Classification of Sensor data","volume":"2130","author":"van laerhoven","year":"2001","journal-title":"Artificial Neural Networks"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/PL00011669"}],"event":{"name":"Third IEEE International Conference on Data Mining","location":"Melbourne, FL, USA","acronym":"ICDM-03"},"container-title":["Third IEEE International Conference on Data Mining"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx5\/8854\/27998\/01250910.pdf?arnumber=1250910","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,16]],"date-time":"2017-06-16T04:35:17Z","timestamp":1497587717000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/1250910\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/icdm.2003.1250910","relation":{},"subject":[]}}