{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T04:02:22Z","timestamp":1746331342346,"version":"3.40.4"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319076911"},{"type":"electronic","value":"9783319076928"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-07692-8_40","type":"book-chapter","created":{"date-parts":[[2014,5,29]],"date-time":"2014-05-29T16:19:57Z","timestamp":1401380397000},"page":"419-429","source":"Crossref","is-referenced-by-count":0,"title":["An Enhanced Parameter-Free Subsequence Time Series Clustering for High-Variability-Width Data"],"prefix":"10.1007","author":[{"given":"Navin","family":"Madicar","sequence":"first","affiliation":[]},{"given":"Haemwaan","family":"Sivaraks","sequence":"additional","affiliation":[]},{"given":"Sura","family":"Rodpongpun","sequence":"additional","affiliation":[]},{"given":"Chotirat Ann","family":"Ratanamahatana","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"40_CR1","doi-asserted-by":"crossref","unstructured":"Keogh, E.J., Lin, J., Truppel, W.: Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 115\u2013122 (2003)","DOI":"10.1109\/ICDM.2003.1250910"},{"key":"40_CR2","unstructured":"Das, G., Lin, K., Mannila, H., Renganathan, G., Smyth, P.: Rule Discovery from Time Series. In: Proceedings of the 3rd Knowledge Discovery and Data Mining (KDD) (1998)"},{"key":"40_CR3","doi-asserted-by":"crossref","unstructured":"Zakaria, J., Mueen, A., Keogh, E.: Clustering Time Series Using Unsupervised-Shapelets. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp. 785\u2013794 (2012)","DOI":"10.1109\/ICDM.2012.26"},{"issue":"6","key":"40_CR4","doi-asserted-by":"publisher","first-page":"2743","DOI":"10.1109\/18.720554","volume":"44","author":"A. Barron","year":"1998","unstructured":"Barron, A., Rissanen, J., Yu, B.: The minimum description length principle in coding and modeling. IEEE Transactions on Information Theory\u00a044(6), 2743\u20132760 (1998)","journal-title":"IEEE Transactions on Information Theory"},{"key":"40_CR5","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.engappai.2010.09.007","volume":"24","author":"T. Fu","year":"2011","unstructured":"Fu, T.: A review on time series data mining. Engineering Applications of Artificial Intelligence\u00a024, 164\u2013181 (2011)","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"40_CR6","doi-asserted-by":"crossref","unstructured":"Rakthanmanon, T., Keogh, E.J., Lonardi, S., Evans, S.: Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring. In: Proceedings of the 11th IEEE International Conference on Data Mining (ICDM), pp. 547\u2013556 (2011)","DOI":"10.1109\/ICDM.2011.146"},{"key":"40_CR7","doi-asserted-by":"crossref","unstructured":"Mueen, A., Keogh, E.J., Zhu, Q., Cash, S., Westover, M.B.: Exact Discovery of Time Series Motifs. In: Proceedings of the SIAM International Conference on Data Mining, pp. 473\u2013484 (2009)","DOI":"10.1137\/1.9781611972795.41"},{"key":"40_CR8","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.knosys.2012.04.022","volume":"35","author":"S. Rodpongpun","year":"2012","unstructured":"Rodpongpun, S., Niennattrakul, V., Ratanamahatana, C.A.: Selective Subsequence Time Series clustering. Knowledge-Based Systems\u00a035, 361\u2013368 (2012)","journal-title":"Knowledge-Based Systems"},{"key":"40_CR9","unstructured":"Keogh, E.J., Xi, X., Wei, L., Ratanamahatana, C.A., The, U.C.R.: The UCR time series classification\/clustering homepage (2008), www.cs.ucr.edu\/~eamonn\/time_series_dat\/"},{"key":"40_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1007\/3-540-46043-8_58","volume-title":"Computational Science - ICCS 2002","author":"P. Cotofrei","year":"2002","unstructured":"Cotofrei, P., Stoffel, K.: Classification Rules + Time = Temporal Rules. In: Sloot, P.M.A., Tan, C.J.K., Dongarra, J., Hoekstra, A.G. (eds.) ICCS-ComputSci 2002, Part I. LNCS, vol.\u00a02329, pp. 572\u2013581. Springer, Heidelberg (2002)"},{"key":"40_CR11","unstructured":"Yingchareonthawornchai, S., Sivaraks,Rodpongpun, S., Ratanamahatana, C.A.: The Proper Length Motif Discovery Algorithm. In: Proceedings of the 16th International Computer Science and Engineering Conference (ICSEC 2012), Chonburi, Thailand (2012)"},{"key":"40_CR12","doi-asserted-by":"crossref","unstructured":"Madicar, N., Sivaraks, H., Rodpongpun, S., Ratanamahatana, C.A.: Parameter-free subsequences time series clustering with various-width clusters. In: 2013 5th International Conference on Knowledge and Smart Technology (KST), pp. 150\u2013155 (2013)","DOI":"10.1109\/KST.2013.6512805"},{"key":"40_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1007\/978-3-642-14640-4_12","volume-title":"New Frontiers in Applied Data Mining","author":"V. Niennattrakul","year":"2010","unstructured":"Niennattrakul, V., Wanichsan, D., Ratanamahatana, C.A.: Accurate Subsequence Matching on Data Stream under Time Warping Distance. In: Theeramunkong, T., Nattee, C., Adeodato, P.J.L., Chawla, N., Christen, P., Lenca, P., Poon, J., Williams, G. (eds.) New Frontiers in Applied Data Mining. LNCS, vol.\u00a05669, pp. 156\u2013167. Springer, Heidelberg (2010)"},{"issue":"4","key":"40_CR14","doi-asserted-by":"publisher","first-page":"43","DOI":"10.4018\/jdwm.2011100103","volume":"7","author":"S. Wang","year":"2011","unstructured":"Wang, S., Gan, W., Li, D., Li, D.: Data Field for Hierarchical Clustering. International Journal of Data Warehousing and Mining archive (IJDWM)\u00a07(4), 43\u201363 (2011)","journal-title":"International Journal of Data Warehousing and Mining archive (IJDWM)"}],"container-title":["Advances in Intelligent Systems and Computing","Recent Advances on Soft Computing and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-07692-8_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T04:57:26Z","timestamp":1746248246000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-07692-8_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319076911","9783319076928"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-07692-8_40","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2014]]}}}