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J.; Keogh, E., iSAX: Indexing and mining terabyte sized time series, In: Proc. 2008 ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (KDD’08) Las Vegas, NV. (Aug. 2008), pp. 623–631.

[SKS10] Silberschatz, A.; Korth, H.F.; Sudarshan, S., Database System Concepts. 6th ed. (2010) McGraw-Hill .

[SLT+01] Shekhar, S.; Lu, C.-T.; Tan, X.; Chawla, S.; Vatsavai, R.R., Map cube: A visualization tool for spatial data warehouses, In: (Editors: Miller, H.J.; Han, J.) Geographic Data Mining and Knowledge Discovery (2001) Taylor and Francis, pp. 73–108.

[SM97] Setubal, J.C.; Meidanis, J., Introduction to Computational Molecular Biology. (1997) PWS Publishing Co. .

[SMT91] Shavlik, J.W.; Mooney, R.J.; Towell, G.G., Symbolic and neural learning algorithms: An experimental comparison, Machine Learning 6 (1991) 111–144.

[SN88] Saito, K.; Nakano, R., Medical diagnostic expert system based on PDP model, In: Proc. 1988 IEEE Int. Conf. Neural Networks San Mateo, CA. (1988), pp. 225–262.

[SOMZ96] Shen, W.; Ong, K.; Mitbander, B.; Zaniolo, C., Metaqueries for data mining, In: (Editors: Fayyad, U.M.; Piatetsky-Shapiro, G.; Smyth, P.; Uthurusamy, R.) Advances in Knowledge Discovery and Data Mining (1996) AAAI/MIT Press, pp. 375–398.

[SON95] Savasere, A.; Omiecinski, E.; Navathe, S., An efficient algorithm for mining association rules in large databases, In: Proc. 1995 Int. Conf. Very Large Data Bases (VLDB’95) Zurich, Switzerland. (Sept. 1995), pp. 432–443.

[SON98] Savasere, A.; Omiecinski, E.; Navathe, S., Mining for strong negative associations in a large database of customer transactions, In: Proc. 1998 Int. Conf. Data Engineering (ICDE’98) Orlando, FL. (Feb. 1998), pp. 494–502.

[SR81] Sokal, R.; Rohlf, F., Biometry. (1981) Freeman .

[SR92] Skowron, A.; Rauszer, C., The discernibility matrices and functions in information systems, In: (Editor: Slowinski, R.) Intelligent Decision Support, Handbook of Applications and Advances of the Rough Set Theory (1992) Kluwer Academic, pp. 331–362.

[SS88] Siedlecki, W.; Sklansky, J., On automatic feature selection, Int. J. Pattern Recognition and Artificial Intelligence 2 (1988) 197–220.

[SS94] Sarawagi, S.; Stonebraker, M., Efficient organization of large multidimensional arrays, In: Proc. 1994 Int. Conf. Data Engineering (ICDE’94) Houston, TX. (Feb. 1994), pp. 328–336.

[SS01] Sathe, G.; Sarawagi, S., Intelligent rollups in multidimensional OLAP data, In: Proc. 2001 Int. Conf. Very Large Data Bases (VLDB’01) Rome, Italy. (Sept. 2001), pp. 531–540.

[SS05] Shumway, R.H.; Stoffer, D.S., Time Series Analysis and Its Applications. (2005) Springer, New York .

[ST96] Silberschatz, A.; Tuzhilin, A., What makes patterns interesting in knowledge discovery systems, IEEE Trans. Knowledge and Data Engineering 8 (Dec. 1996) 970–974.

[STA98] Sarawagi, S.; Thomas, S.; Agrawal, R., Integrating association rule mining with relational database systems: Alternatives and implications, In: Proc. 1998 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’98) Seattle, WA. (June 1998), pp. 343–354.

[STH+10] Sun, Y.; Tang, J.; Han, J.; Gupta, M.; Zhao, B., Community evolution detection in dynamic heterogeneous information networks, In: Proc. 2010 KDD Workshop Mining and Learning with Graphs (MLG’10) Washington, DC. (July 2010).

[Ste72] Stefansky, W., Rejecting outliers in factorial designs, Technometrics 14 (1972) 469–479.

[Sto74] Stone, M., Cross-validatory choice and assessment of statistical predictions, J. Royal Statistical Society 36 (1974) 111–147.

[SVA97] Srikant, R.; Vu, Q.; Agrawal, R., Mining association rules with item constraints, In: Proc. 1997 Int. Conf. Knowledge Discovery and Data Mining (KDD’97) Newport Beach, CA. (Aug. 1997), pp. 67–73.

[SW49] Shannon, C.E.; Weaver, W., The Mathematical Theory of Communication. (1949) University of Illinois Press .

[Swe88] Swets, J., Measuring the accuracy of diagnostic systems, Science 240 (1988) 1285–1293.

[Swi98] Swiniarski, R., Rough sets and principal component analysis and their applications in feature extraction and selection, data model building and

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