{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T14:44:06Z","timestamp":1769265846127,"version":"3.49.0"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2013,12,1]],"date-time":"2013-12-01T00:00:00Z","timestamp":1385856000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"DOI":"10.1007\/s10844-013-0290-3","type":"journal-article","created":{"date-parts":[[2013,11,30]],"date-time":"2013-11-30T02:06:46Z","timestamp":1385777206000},"source":"Crossref","is-referenced-by-count":5,"title":["TS-stream: clustering time series on data streams"],"prefix":"10.1007","author":[{"given":"C\u00e1ssio M. M.","family":"Pereira","sequence":"first","affiliation":[]},{"given":"Rodrigo F.","family":"de Mello","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,12,1]]},"reference":[{"key":"290_CR1","unstructured":"Aggarwal, C.C., Han, J., Wang, J., Yu, P.S. (2003). A framework for clustering evolving data streams. In: VLDB \u20192003: Proceedings of the 29th international conference on very large data bases (pp. 81\u201392). VLDB Endowment."},{"key":"290_CR2","unstructured":"Aggarwal, C.C., Han, J.,Wang, J., Yu, P.S. (2004). A framework for projected clustering of high dimensional data streams. In VLDB \u201904: Proceedings of the 30th international conference on very large data bases (pp. 852\u2013863). VLDB Endowment."},{"key":"290_CR3","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/T-C.1974.223784","volume":"23","author":"N Ahmed","year":"1974","unstructured":"Ahmed, N., Natarajan, T., Rao, K.R. (1974). Discrete cosine transfom. IEEE Transactions on Computers, 23, 90\u201393.","journal-title":"IEEE Transactions on Computers"},{"key":"290_CR4","unstructured":"Appel, G. (2005). Technical analysis: power tools for active investors, 1st edn, FT Press."},{"issue":"1","key":"290_CR5","first-page":"27","volume":"3","author":"D Ardia","year":"2011","unstructured":"Ardia, D., Boudt, K., Carl, P., Mullen, K.M., Peterson, B.G. (2011). Differential Evolution with DEoptim: An application to non-convex portfolio optimization. The Royal Journal, 3(1), 27\u201334.","journal-title":"The Royal Journal"},{"key":"290_CR6","doi-asserted-by":"crossref","unstructured":"Athanassioum, P. (2012). Research handbook on hedge funds, private equity and alternative investments, Edward Elgar Pub.","DOI":"10.4337\/9781849806084"},{"key":"290_CR7","doi-asserted-by":"crossref","unstructured":"B\u00e9lisle, C. (1992). Convergence theorems for a class of simulated annealing algorithms on rd. Journal of Applied Probability, 885\u2013895.","DOI":"10.2307\/3214721"},{"key":"290_CR8","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.datak.2005.05.009","volume":"58","author":"J Beringer","year":"2006","unstructured":"Beringer, J., & H\u00fcllermeier, E. (2006). Online clustering of parallel data streams. Data Knowledge Engineering, 58, 180\u2013204. doi: 10.1016\/j.datak.2005.05.009 .","journal-title":"Data Knowledge Engineering"},{"key":"290_CR9","unstructured":"Bifet, A., & Kirby, R. (2009). Data stream mining: A practical approach. Technical report, The University of Waikato."},{"key":"290_CR10","doi-asserted-by":"crossref","unstructured":"Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. The journal of political economy, 637\u2013654.","DOI":"10.1086\/260062"},{"key":"290_CR11","unstructured":"Box, G., & Jenkins, G. (1994). Time series analysis: forecasting and control, Prentice Hall PTR."},{"key":"290_CR12","doi-asserted-by":"crossref","unstructured":"Cao, F. (2006). Density-based clustering over an evolving data stream with noise. In Proceedings of the 6th SIAM international conference data mining.","DOI":"10.1137\/1.9781611972764.29"},{"key":"290_CR13","unstructured":"Chaovalit, P. (2009). Clustering transient data streams by example and by variable. PhD thesis, University of Maryland."},{"key":"290_CR14","unstructured":"Chatfield, C. (2003). The analysis of time series: an introduction (Vol. 59). CRC press."},{"key":"290_CR15","doi-asserted-by":"crossref","unstructured":"Daubechies, I. (1992). Ten lectures on wavelets. Society for industrial and applied mathematics, Philadelphia.","DOI":"10.1137\/1.9781611970104"},{"key":"290_CR16","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s00357-010-9064-6","volume":"27","author":"SP D\u00edaz","year":"2010","unstructured":"D\u00edaz, S.P., & Vilar, J.A. (2010). Comparing several parametric and nonparametric approaches to time series clustering: a simulation study. Journal of Classification, 27, 333\u2013362. doi: 10.1007\/s00357-010-9064-6 .","journal-title":"Journal of Classification"},{"issue":"12","key":"290_CR17","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1038\/nbt1205-1499","volume":"23","author":"P D\u2019haeseleer","year":"2005","unstructured":"D\u2019haeseleer, P., et al. (2005). How does gene expression clustering work? Nature biotechnology, 23(12), 1499\u20131502.","journal-title":"Nature biotechnology"},{"key":"290_CR18","unstructured":"Fourier, J. (1888). Th\u00e9orie analytique de la chaleur (Vol. 1). Gauthier-Villars et fils."},{"key":"290_CR19","doi-asserted-by":"crossref","unstructured":"Fu, T.C. (2011). A review on time series data mining. Engineering Applications of Artificial Intelligence, 24(1), 164\u2013181. doi: 10.1016\/j.engappai.2010.09.007 , http:\/\/www.sciencedirect.com\/science\/article\/B6V2M-516KF3X-1\/2\/f93f19227049b30e34b3de788e9e2b7f .","DOI":"10.1016\/j.engappai.2010.09.007"},{"issue":"4","key":"290_CR20","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1142\/S0219720009004230","volume":"7","author":"A Fujita","year":"2009","unstructured":"Fujita, A., Sato, J., Demasi, M., Sogayar, M., Ferreira, C., Miyano, S. (2009). Comparing pearson, spearman and hoeffding\u2019s d measure for gene expression association analysis. Journal of Bioinformatics and Computational Biology, 7(4), 663\u201384.","journal-title":"Journal of Bioinformatics and Computational Biology"},{"key":"290_CR21","unstructured":"Gama, J. (2010). Knowledge discovery from data streams, 1st edn. Chapman & Hall\/CRC."},{"key":"290_CR22","unstructured":"Hilbert, D. (1912). Grundz\u00fcge einer allgemeinen Theorie der linearen Integralgleichungen. BG Teubner."},{"key":"290_CR23","doi-asserted-by":"crossref","unstructured":"Hoeffding, W. (1963). Probability inequalities for sums of bounded random variables. Journal of the American Statistical Association, 13\u201330.","DOI":"10.1080\/01621459.1963.10500830"},{"issue":"1971","key":"290_CR24","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","volume":"454","author":"N Huang","year":"1998","unstructured":"Huang, N., Shen, Z., Long, S., Wu, M., Shih, H., Zheng, Q., Yen, N., Tung, C., Liu, H. (1998). The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 454(1971), 903.","journal-title":"Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences"},{"key":"290_CR25","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF01908075","volume":"2","author":"L Hubert","year":"1985","unstructured":"Hubert, L., & Arabie, P. (1985). Comparing partitions. Journal of Classification, 2, 193\u2013218. doi: 10.1007\/BF01908075 .","journal-title":"Journal of Classification"},{"key":"290_CR26","first-page":"1","volume":"1","author":"RP Ishii","year":"2011","unstructured":"Ishii, R.P., Rios, R.A., de Mello, R.F. (2011). Classification of time series generation processes using experimental tools: a survey and proposal of an automatic and systematic approach. International Journal of Computational Science and Engineering, 1, 1\u201321.","journal-title":"International Journal of Computational Science and Engineering"},{"key":"290_CR27","unstructured":"Kantz, H., & Schreiber, T. (1997). Nonlinear time series analysis. New York: Cambridge University Press."},{"key":"290_CR28","unstructured":"Keogh, E., Lin, J., Truppel, W. (2003). Clustering of time series subsequences is meaningless: implications for previous and future research. In ICDM \u201903: Proceedings of the 3rd IEEE international conference on data mining, IEEE computer society (pp. 115\u2013). Washington, DC. http:\/\/dl.acm.org\/citation.cfm?id=951949.952156 ."},{"issue":"2","key":"290_CR29","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.is.2007.09.001","volume":"33","author":"M Kontaki","year":"2008","unstructured":"Kontaki, M., Papadopoulos, A.N., Manolopoulos, Y. (2008). Continuous subspace clustering in streaming time series. Information Systems, 33(2), 240\u2013260.","journal-title":"Information Systems"},{"issue":"2","key":"290_CR30","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s10115-010-0342-8","volume":"29","author":"P Kranen","year":"2011","unstructured":"Kranen, P., Assent, I., Baldauf, C., Seidl, T. (2011). The clustree: indexing micro-clusters for anytime stream mining. Knowledge and Information Systems, 29(2), 249\u2013272. doi: 10.1007\/s10115-010-0342-8 .","journal-title":"Knowledge and Information Systems"},{"issue":"2","key":"290_CR31","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1175\/1520-0469(1963)020<0130:DNF>2.0.CO;2","volume":"20","author":"EN Lorenz","year":"1963","unstructured":"Lorenz, E.N. (1963). Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20(2), 130\u2013141.","journal-title":"Journal of the Atmospheric Sciences"},{"key":"290_CR32","volume-title":"Information theory, inference, and learning algorithms","author":"D MacKay","year":"2003","unstructured":"MacKay, D. (2003). Information theory, inference, and learning algorithms. Cambridge: Cambridge University Press."},{"issue":"5-6","key":"290_CR33","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.physrep.2006.11.001","volume":"438","author":"N Marwan","year":"2007","unstructured":"Marwan, N., Romano, M.C., Thiel, M., Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5-6), 237\u2013329. doi: 10.1016\/j.physrep.2006.11.001 .","journal-title":"Physics Reports"},{"key":"290_CR34","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1103\/PhysRevE.49.1685","volume":"49","author":"C Peng","year":"1994","unstructured":"Peng, C., Buldyrev, S., Havlin, S., Simons, M., Stanley, H., Goldberger, A. (1994). On the mosaic organization of DNA sequences. Physical Review E, 49, 1685\u20131689.","journal-title":"Physical Review E"},{"issue":"3","key":"290_CR35","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1007\/BF01054341","volume":"73","author":"B Pompe","year":"1993","unstructured":"Pompe, B. (1993). Measuring statistical dependences in a time series. Journal of Statistical Physics, 73(3), 587\u2013610.","journal-title":"Journal of Statistical Physics"},{"issue":"1","key":"290_CR36","first-page":"81","volume":"1","author":"J Quinlan","year":"1986","unstructured":"Quinlan, J. (1986). Induction of decision trees. Machine learning, 1(1), 81\u2013106.","journal-title":"Machine learning"},{"key":"290_CR37","unstructured":"Quinlan, J. (1993). C4. 5: programs for machine learning, Morgan Kaufmann."},{"key":"290_CR38","unstructured":"R Development Core Team (2011). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. http:\/\/www.R-project.org , ISBN 3-900051-07-0."},{"key":"290_CR39","unstructured":"Ren, J., Cai, B., Hu, C. (2011). Clustering over data streams based on grid density and index tree. Journal of Convergence Information Technology, 6(1)."},{"key":"290_CR40","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1109\/TKDE.2007.190727","volume":"20","author":"PP Rodrigues","year":"2008","unstructured":"Rodrigues, P.P., Gama, J., Pedroso, J. (2008). Hierarchical clustering of time-series data streams. IEEE Transactions on Knowledge and Data Engineering, 20, 615\u2013627. doi: 10.1109\/TKDE.2007.190727 .","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"3","key":"290_CR41","first-page":"78","volume":"6","author":"M Sandri","year":"1996","unstructured":"Sandri, M. (1996). Numerical calculation of lyapunov exponents. The Mathematical Journal, 6(3), 78\u201384.","journal-title":"The Mathematical Journal"},{"key":"290_CR42","volume-title":"The algorithm design manual","author":"SS Skiena","year":"1998","unstructured":"Skiena, S.S. (1998). The algorithm design manual. New York: Springer."},{"key":"290_CR43","doi-asserted-by":"crossref","unstructured":"Takens, F. (1981). Detecting strange attractors in turbulence. Dynamical systems and turbulence, (pp. 366\u2013381). Warwick 1980.","DOI":"10.1007\/BFb0091924"},{"key":"290_CR44","unstructured":"Tan, P.N., Steinbach, M., Kumar, V. (2005). Introduction to Data Mining. Boston: Addison-Wesley Longman."},{"key":"290_CR45","doi-asserted-by":"crossref","unstructured":"Tang, L.A., Zheng, Y., Yuan, J., Han, J., Leung, A., Hung, C.C., Peng, W.C. (2012). On discovery of traveling companions from streaming trajectories. In 2012 IEEE 28th International Conference on Data Engineering (ICDE), (pp. 186-197). IEEE.","DOI":"10.1109\/ICDE.2012.33"},{"key":"290_CR46","doi-asserted-by":"crossref","unstructured":"Vinh, N.X., Epps, J., Bailey, J. (2009). Information theoretic measures for clusterings comparison: is a correction for chance necessary? In ICML \u201909 (pp 1073\u20131080). New York: ACM. doi: 10.1145\/1553374.1553511 .","DOI":"10.1145\/1553374.1553511"},{"key":"290_CR47","volume-title":"Probability and statistics for engineers and scientists","author":"R Walpole","year":"1998","unstructured":"Walpole, R., Myers, R., Myers, S., Ye, K. (1998). Probability and statistics for engineers and scientists. Upper Saddle River: Prentice Hall."},{"issue":"3","key":"290_CR48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1552303.1552307","volume":"3","author":"L Wan","year":"2009","unstructured":"Wan, L., Ng, W.K., Dang, X.H., Yu, P.S., Zhang, K. (2009). Density-based clustering of data streams at multiple resolutions. ACM Transactions on Knowledge and Discovery Data, 3(3), 1\u201328. doi: 10.1145\/1552303.1552307 .","journal-title":"ACM Transactions on Knowledge and Discovery Data"},{"issue":"3","key":"290_CR49","doi-asserted-by":"crossref","first-page":"645","DOI":"10.2307\/1968482","volume":"37","author":"H Whitney","year":"1936","unstructured":"Whitney, H. (1936). Differentiable manifolds. Annals of Mathematics, 37(3), 645\u2013680.","journal-title":"Annals of Mathematics"},{"key":"290_CR50","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/978-3-642-20847-8_14","volume-title":"Proceedings of the 15th Pacific-Asia conference on advances in knowledge discovery and data mining","author":"H Widiputra","year":"2011","unstructured":"Widiputra, H., Pears, R., Kasabov, N. (2011). Multiple time-series prediction through multiple time-series relationships profiling and clustered recurring trends. In Proceedings of the 15th Pacific-Asia conference on advances in knowledge discovery and data mining (pp. 161\u2013172). Berlin, Heidelberg: Springer-Verlag."},{"key":"290_CR51","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1109\/TKDE.2010.112","volume":"23","author":"Y Yang","year":"2011","unstructured":"Yang, Y., & Chen, K. (2011). Temporal data clustering via weighted clustering ensemble with different representations. IEEE Transactions on Knowledge and Data Engineering, 23, 307\u2013320.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"290_CR52","doi-asserted-by":"crossref","unstructured":"Zheng, K., Zheng, Y., Yuan, N.J., Shang, S. (2013). On discovery of gathering patterns from trajectories. In IEEE international conference on data engineering, ICDE.","DOI":"10.1109\/ICDE.2013.6544829"}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-013-0290-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10844-013-0290-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-013-0290-3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,4]],"date-time":"2019-08-04T07:56:55Z","timestamp":1564905415000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10844-013-0290-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12,1]]},"references-count":52,"alternative-id":["290"],"URL":"https:\/\/doi.org\/10.1007\/s10844-013-0290-3","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"value":"0925-9902","type":"print"},{"value":"1573-7675","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,12,1]]}}}