{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T12:34:35Z","timestamp":1742992475316,"version":"3.40.3"},"publisher-location":"New York, NY","reference-count":70,"publisher":"Springer New York","isbn-type":[{"type":"print","value":"9780387758886"},{"type":"electronic","value":"9780387304403"}],"license":[{"start":{"date-parts":[[2009,1,1]],"date-time":"2009-01-01T00:00:00Z","timestamp":1230768000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2009,1,1]],"date-time":"2009-01-01T00:00:00Z","timestamp":1230768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"DOI":"10.1007\/978-0-387-30440-3_301","type":"book-chapter","created":{"date-parts":[[2009,6,17]],"date-time":"2009-06-17T15:59:09Z","timestamp":1245254349000},"page":"5051-5064","source":"Crossref","is-referenced-by-count":3,"title":["Knowledge Discovery: Clustering"],"prefix":"10.1007","author":[{"given":"Pavel","family":"Berkhin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Inderjit S.","family":"Dhillon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"301_CR1_301","doi-asserted-by":"crossref","unstructured":"Aggarwal CC, Wolf JL, Yu PS, Procopiuc C, Park JS (1999) Fast algorithms for projected clustering. In: Proceedings ACM SIGMOD International Conference on Management of Data, Philadelphia, pp\u00a061\u201372","DOI":"10.1145\/304181.304188"},{"key":"301_CR2_301","doi-asserted-by":"crossref","unstructured":"Agrawal R, Gehrke J, Gunopulos D, Raghavan P (1998) Automatic subspace clustering of high dimensional data for data mining applications. In: Proceedings of ACM SIGMOD, Seattle, pp\u00a094\u2013105","DOI":"10.1145\/276305.276314"},{"key":"301_CR3_301","doi-asserted-by":"crossref","unstructured":"Ankerst M, Breunig MM, Kriegel HP, Sander J (1999) Optics: Ordering points to identify the clustering structure. In: Proceedings ACM SIGMOD International Conference on Management of Data, Philadelphia, pp\u00a049\u201360","DOI":"10.1145\/304181.304187"},{"key":"301_CR4_301","first-page":"1705","volume":"6","author":"A Banerjee","year":"2005","unstructured":"Banerjee A, Merugu S, Dhillon I, Ghosh J (2005) Clustering with Bregman divergences. J\u00a0Mach Learn Res (JMLR) 6:1705\u20131749","journal-title":"J Mach Learn Res (JMLR)"},{"key":"301_CR5_301","first-page":"1919","volume":"8","author":"A Banerjee","year":"2007","unstructured":"Banerjee A, Dhillon I, Ghosh J, Merugu S, Modha D (2007) A\u00a0generalized maximum entropy approach to Bregman co\u2010clustering and matrix approximation. J\u00a0Mach Learn Res(JMLR) 8:1919\u20131986","journal-title":"J Mach Learn Res(JMLR)"},{"key":"301_CR6_301","doi-asserted-by":"crossref","unstructured":"Barbara D, Chen P (2000) Using the fractal dimension to cluster datasets. In: Proceedings of the 6th ACM SIGKDD, Boston, pp\u00a0260\u2013264","DOI":"10.1145\/347090.347145"},{"key":"301_CR7_301","unstructured":"Berkhin P (2005) A\u00a0survey of clustering data mining techniques. In: Kogan J, Nicholas C, Teboulle M (eds) Grouping Multidimensional Data. Springer"},{"key":"301_CR8_301","doi-asserted-by":"crossref","unstructured":"Berkhin P, Becher JD (2002) Learning simple relations: Theory and applications. In: Proceeding Second SIAM International Conference on Data Mining, Arlington, pp\u00a0420\u2013436","DOI":"10.1137\/1.9781611972726.25"},{"issue":"4","key":"301_CR9_301","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1023\/A:1009740529316","volume":"2","author":"DL Boley","year":"1998","unstructured":"Boley DL (1998) Principal direction divisive partitioning. Data Min Knowl Discov 2(4):325\u2013344","journal-title":"Data Min Knowl Discov"},{"key":"301_CR10_301","first-page":"91","volume-title":"Proceedings of the Fifteenth International Conference on Machine Learning (ICML)","author":"P Bradley","year":"1998","unstructured":"Bradley P, Fayyad U (1998) Refining initial points for k\u2011means clustering. In: Shavlik J (ed) Proceedings of the Fifteenth International Conference on Machine Learning (ICML). AAAI Press, San Francisco, pp\u00a091\u201399"},{"key":"301_CR11_301","volume-title":"Proceedings Fourth International Conference on Knowledge Discovery and Data Mining","author":"P Bradley","year":"1998","unstructured":"Bradley P, Fayyad U, Reina C (1998) Scaling clustering algorithms to large databases. In: Proceedings Fourth International Conference on Knowledge Discovery and Data Mining. AAAI Press, San Francisco"},{"key":"301_CR12_301","doi-asserted-by":"crossref","unstructured":"Cadez I, Gaffney S, Smyth P (2000) A\u00a0general probabilistic framework for clustering individuals. Tech Rep UCI-ICS 00-09. University of California, Irvine","DOI":"10.1145\/347090.347119"},{"key":"301_CR13_301","doi-asserted-by":"crossref","unstructured":"Cadez I, Smyth P, Mannila H (2001) Probabilistic modeling of transactional data with applications to profiling, visualization, and prediction. In: Proceedings of the 7th ACM SIGKDD, San Francisco, pp\u00a037\u201346","DOI":"10.1145\/502512.502523"},{"key":"301_CR14_301","doi-asserted-by":"crossref","unstructured":"Chan P, Schlag M, Zien J (1994) Spectral k\u2011way ratio cut partitioning. IEEE Trans CAD\u2010Integr Circuits Syst 13:1088\u20131096","DOI":"10.1109\/43.310898"},{"key":"301_CR15_301","unstructured":"Cheeseman P, Stutz J (1996) Bayesian classification (autoclass): Theory and results. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds) Advances in Knowledge Discovery and Data Mining. AAAI\/MIT Press, pp\u00a0153\u2013180"},{"key":"301_CR16_301","doi-asserted-by":"crossref","unstructured":"Cheng C, Fu A, Zhang Y (1999) Entropy\u2010based subspace clustering for mining numerical data. In: Proceedings of the 5th ACM SIGKDD, San Diego, pp\u00a084\u201393","DOI":"10.1145\/312129.312199"},{"key":"301_CR17_301","volume-title":"Elements of Information Theory","author":"TM Cover","year":"1991","unstructured":"Cover TM, Thomas JA (1991) Elements of Information Theory. Wiley, New York"},{"issue":"7","key":"301_CR18_301","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/BF01890115","volume":"1","author":"W Day","year":"1984","unstructured":"Day W, Edelsbrunner H (1984) Efficient algorithms for agglomerative hierarchical clustering methods. J\u00a0Classif 1(7):7\u201324","journal-title":"J Classif"},{"key":"301_CR19_301","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1093\/comjnl\/20.4.364","volume":"20","author":"D Defays","year":"1977","unstructured":"Defays D (1977) An efficient algorithm for a\u00a0complete link method. Comp J 20:364\u2013366","journal-title":"Comp J"},{"key":"301_CR20_301","doi-asserted-by":"crossref","unstructured":"Dhillon IS (2001) Co\u2010clustering documents and words using bipartite spectral graph partitioning. In: Proceedings of the The Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD-2001). Also appears as: UT CS Technical Report # TR 2001-05, March, 1999","DOI":"10.1145\/502512.502550"},{"key":"301_CR21_301","doi-asserted-by":"crossref","unstructured":"Dhillon IS, Mallela S, Kumar R (2003) A\u00a0divisive information\u2010theoretic feature clustering algorithm for text classification. J\u00a0Mach Learn Res (JMLR): Var Feature Sel Special Issue 3:1265\u20131287","DOI":"10.1145\/956750.956764"},{"issue":"11","key":"301_CR22_301","doi-asserted-by":"crossref","first-page":"1944","DOI":"10.1109\/TPAMI.2007.1115","volume":"29","author":"IS Dhillon","year":"2007","unstructured":"Dhillon IS, Guan Y, Kulis B (2007) Weighted graph cuts without eigenvectors: A\u00a0multilevel approach. IEEE Trans Pattern Anal Mach Intell 29(11):1944\u20131957","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"301_CR23_301","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1147\/rd.175.0420","volume":"17","author":"WE Donath","year":"1973","unstructured":"Donath WE, Hoffman AJ (1973) Lower bounds for the partitioning of graphs. IBM J Res Dev 17:422\u2013425","journal-title":"IBM J Res Dev"},{"key":"301_CR24_301","doi-asserted-by":"crossref","unstructured":"DuMouchel W, Volinsky C, Johnson T, Cortes C, Pregibon D (1999) Squashing flat files flatter. In: Proceedings of the 5th ACM SIGKDD, San Diego, pp\u00a06\u201315","DOI":"10.1145\/312129.312184"},{"key":"301_CR25_301","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1142\/9789814343138_0001","volume-title":"Handbook of Pattern Recognition and Computer Vision","author":"R Dubes","year":"1993","unstructured":"Dubes R (1993) Cluster analysis and related issues. In: Chen C, Pau L, Wang P (eds) Handbook of Pattern Recognition and Computer Vision. World Scientific, River Edge, pp\u00a03\u201332"},{"key":"301_CR26_301","unstructured":"Ester M, Kriegel HP, Xu X (1995) A\u00a0database interface for clustering in large spatial databases. In: Proceedings of the 1st ACM SIGKDD, Montreal, pp\u00a094\u201399"},{"key":"301_CR27_301","unstructured":"Ester M, Kriegel HP, Sander J, Xu X (1996) A\u00a0density\u2010based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the 2nd ACM SIGKDD, Portland, pp\u00a0226\u2013231"},{"key":"301_CR28_301","volume-title":"Cluster Analysis","author":"B Everitt","year":"1993","unstructured":"Everitt B (1993) Cluster Analysis, 3rd edn. Edward Arnold, London","edition":"3"},{"key":"301_CR29_301","doi-asserted-by":"crossref","first-page":"619","DOI":"10.21136\/CMJ.1975.101357","volume":"25","author":"M Fiedler","year":"1975","unstructured":"Fiedler M (1975) A\u00a0property of eigenvectors of non\u2010negative symmetric matrices and its application to graph theory. Czech Math J 25:619\u2013633","journal-title":"Czech Math J"},{"key":"301_CR30_301","doi-asserted-by":"crossref","unstructured":"Ganti V, Gehrke J, Ramakrishnan R (1999) CACTUS\u2010clustering categorical data using summaries. In: Proceedings of the 5th ACM SIGKDD, San Diego, pp\u00a073\u201383","DOI":"10.1145\/312129.312201"},{"key":"301_CR31_301","doi-asserted-by":"crossref","unstructured":"Ganti V, Ramakrishnan R, Gehrke J, Powell A, French J (1999) Clustering large datasets in arbitrary metric spaces. In: Proceedings of the 15th ICDE, Sydney, pp\u00a0502\u2013511","DOI":"10.1109\/ICDE.1999.754966"},{"key":"301_CR32_301","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4615-3626-0","volume-title":"Vector quantization and signal compression","author":"A Gersho","year":"1992","unstructured":"Gersho A, Gray RM (1992) Vector quantization and signal compression. Kluwer, Dordrecht"},{"key":"301_CR33_301","unstructured":"Ghosh J (2003) Scalable clustering methods for data mining. In: Ye N (ed) Handbook of Data Mining. Lawrence Ealbaum Assoc, pp\u00a0247\u2013277"},{"key":"301_CR34_301","unstructured":"Gibson D, Kleinberg J, Raghavan P (1998) Clustering categorical data: An approach based on dynamic systems. In: Proceedings of the 24th International Conference on Very Large Databases, New York, pp\u00a0311\u2013323"},{"key":"301_CR35_301","volume-title":"MAFIA: Efficient and scalable subspace clustering for very large data sets. Tech Rep CPDC-TR-9906-010","author":"S Goil","year":"1999","unstructured":"Goil S, Nagesh H, Choudhary A (1999) MAFIA: Efficient and scalable subspace clustering for very large data sets. Tech Rep CPDC-TR-9906-010. Northwestern University, Evanston"},{"key":"301_CR36_301","doi-asserted-by":"crossref","unstructured":"Guha S, Rastogi R, Shim K (1998) CURE: A\u00a0clustering algorithm for large databases. ACM SIGMOD International Conference on Management of Data, pp\u00a073\u201384","DOI":"10.1145\/276305.276312"},{"issue":"3","key":"301_CR37_301","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1287\/mnsc.17.3.219","volume":"11","author":"KM Hall","year":"1970","unstructured":"Hall KM (1970) A\u00a0r\u2011dimensional quadratic placement algorithm. Manag Sci 11(3):219\u2013229","journal-title":"Manag Sci"},{"key":"301_CR38_301","unstructured":"Han EH, Karypis G, Kumar V, Mobasher B (1997) Clustering based on association rule hypergraphs. In: SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, (SIGMOD-DMKD'97)"},{"key":"301_CR39_301","volume-title":"Data Mining: Concepts and Techniques","author":"J Han","year":"2001","unstructured":"Han J, Kamber M (2001) Data Mining: Concepts and Techniques. Morgan Kaufmann, San Mateo"},{"key":"301_CR40_301","unstructured":"Han J, Kamber M, Tung AKH (2001) Spatial clustering methods in data mining: A\u00a0survey. In: Miller H, Han J (eds) Geographic Data Mining and Knowledge Discovery. Taylor and Francis"},{"key":"301_CR41_301","volume-title":"A multilevel algorithm for partitioning graphs. Tech Rep SAND93-1301","author":"B Hendrickson","year":"1993","unstructured":"Hendrickson B, Leland R (1993) A\u00a0multilevel algorithm for partitioning graphs. Tech Rep SAND93-1301, Sandia National Laboratories, Albuquerque"},{"key":"301_CR42_301","unstructured":"Hinneburg A, Keim D (1998) An efficient approach to clustering large multimedia databases with noise. In: Proceedings of the 4th ACM SIGKDD, New York, pp\u00a058\u201365"},{"issue":"3","key":"301_CR43_301","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"A Jain","year":"1999","unstructured":"Jain A, Murty M, Flynn PJ (1999) Data clustering: A\u00a0review. ACM Comp Surv 31(3):264\u2013323","journal-title":"ACM Comp Surv"},{"key":"301_CR44_301","volume-title":"Algorithms for Clustering Data","author":"AK Jain","year":"1988","unstructured":"Jain AK, Dubes RC (1988) Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs"},{"issue":"8","key":"301_CR45_301","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/2.781637","volume":"32","author":"G Karypis","year":"1999","unstructured":"Karypis G, Han EH, Kumar V (1999) CHAMELEON: Hierarchical clustering using dynamic modeling. IEEE Comput 32(8):68\u201375","journal-title":"IEEE Comput"},{"issue":"1","key":"301_CR46_301","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1137\/S1064827595287997","volume":"20","author":"G Karypis","year":"1999","unstructured":"Karypis G, Kumar V (1999) A\u00a0fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J Sci Comput 20(1):359\u2013392","journal-title":"SIAM J Sci Comput"},{"key":"301_CR47_301","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316801","volume-title":"Finding Groups in Data: An Introduction to Cluster Analysis","author":"L Kaufman","year":"1990","unstructured":"Kaufman L, Rousseeuw P (1990) Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York"},{"issue":"2","key":"301_CR48_301","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1002\/j.1538-7305.1970.tb01770.x","volume":"49","author":"B Kernighan","year":"1970","unstructured":"Kernighan B, Lin S (1970) An efficient heuristic procedure for partitioning graphs. Bell Syst Tech J 49(2):291\u2013307","journal-title":"Bell Syst Tech J"},{"key":"301_CR49_301","unstructured":"Kleinberg J (2002) An impossibility theorem for clustering. In: Proc Neural Info. Processing Systems (NIPS 15)"},{"key":"301_CR50_301","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/5.58325","volume":"9","author":"T Kohonen","year":"1990","unstructured":"Kohonen T (1990) The self\u2010organizing map. Proc IEEE 9:1464\u20131479","journal-title":"Proc IEEE"},{"key":"301_CR51_301","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1093\/comjnl\/9.4.373","volume":"9","author":"G Lance","year":"1967","unstructured":"Lance G, Williams W (1967) A\u00a0general theory of classification sorting strategies. Comp J 9:373\u2013386","journal-title":"Comp J"},{"issue":"6","key":"301_CR52_301","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1145\/331524.331526","volume":"46","author":"T Leighton","year":"1999","unstructured":"Leighton T, Rao S (1999) Multicommodity max\u2010flow min\u2010cut theorems and their use in designing approximation algorithms. J\u00a0ACM 46(6):787\u2013832","journal-title":"J ACM"},{"key":"301_CR53_301","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.21236\/ADA271691","volume-title":"Some extensions of the k\u2011means algorithm for image segmentation and pattern classification. Tech Rep AI Memo","author":"J Marroquin","year":"1993","unstructured":"Marroquin J, Girosi F (1993) Some extensions of the k\u2011means algorithm for image segmentation and pattern classification. Tech Rep AI Memo, MIT, Cambridge, p\u00a01390"},{"key":"301_CR54_301","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511814075","volume-title":"Randomized Algorithms","author":"R Motwani","year":"1995","unstructured":"Motwani R, Raghavan P (1995) Randomized Algorithms. Cambridge University Press, Cambridge"},{"key":"301_CR55_301","unstructured":"Ng A, Jordan M, Weiss Y (2001) On spectral clustering: Analysis and an algorithm. In: Proc Neural Info Proc Syst (NIPS), Vancouver"},{"key":"301_CR56_301","unstructured":"Ng R, Han J (1994) Efficient and effective clustering methods for spatial data mining. In: Proc of the 20th Int Conf on Very Large Data Bases (VLDB), Santiago, pp\u00a0144\u2013155"},{"key":"301_CR57_301","volume-title":"The Symmetric Eigenvalue Problem","author":"B Parlett","year":"1997","unstructured":"Parlett B (1997) The Symmetric Eigenvalue Problem, 2nd edn. SIAM, Philadelphia","edition":"2"},{"key":"301_CR58_301","doi-asserted-by":"crossref","unstructured":"Schikuta E, Erhart M (1997) The BANG\u2010clustering system: grid\u2010based data analysis. In: Proceeding of Advances in Intelligent Data Analysis, Reasoning about Data, 2nd International Symposium, London, pp\u00a0513\u2013524","DOI":"10.1007\/BFb0052867"},{"key":"301_CR59_301","unstructured":"Sheikholeslami G, Chatterjee S, Zhang A (1998) Wavecluster: A\u00a0multi\u2010resolution clustering approach for very large spatial databases. In: Proceedings of the 24th Conference on VLDB, New York, pp\u00a0428\u2013439"},{"issue":"8","key":"301_CR60_301","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888\u2013905","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"301_CR61_301","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1093\/comjnl\/16.1.30","volume":"16","author":"R Sibson","year":"1973","unstructured":"Sibson R (1973) SLINK: An optimally efficient algorithm for the single link cluster method. Comput J 16:30\u201334","journal-title":"Comput J"},{"key":"301_CR62_301","volume-title":"Cluster Analysis Algorithms","author":"H Spath","year":"1980","unstructured":"Spath H (1980) Cluster Analysis Algorithms. Ellis Horwood, Chichester"},{"key":"301_CR63_301","doi-asserted-by":"crossref","unstructured":"Tung A, Hou J, Han J (2001) Spatial clustering in the presence of obstacles. In: Proceedings of the 17th ICDE, Heidelberg, pp\u00a0359\u2013367","DOI":"10.1109\/ICDE.2001.914848"},{"issue":"6","key":"301_CR64_301","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/0306-4573(86)90097-X","volume":"22","author":"EM Voorhees","year":"1986","unstructured":"Voorhees EM (1986) Implementing agglomerative hierarchical clustering algorithms for use in document retrieval. Inf Proc Manag 22(6):465\u2013476","journal-title":"Inf Proc Manag"},{"key":"301_CR65_301","unstructured":"Wang W, Yang J, Muntz R (1997) STING: a\u00a0statistical information grid approach to spatial data mining. In: Proceedings of the 23rd Conference on VLDB, Athens, pp\u00a0186\u2013195"},{"key":"301_CR66_301","unstructured":"Xu X, Ester M, Kriegel HP, Sander J (1998) A\u00a0distribution\u2010based clustering algorithm for mining large spatial datasets. In: Proceedings of the 14th ICDE, Orlando, pp\u00a0324\u2013331"},{"issue":"4","key":"301_CR67_301","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1137\/0211059","volume":"11","author":"A Yao","year":"1982","unstructured":"Yao A (1982) On constructing minimum spanning trees in k\u2011dimensional space and related problems. SIAM J Comput 11(4):721\u2013736","journal-title":"SIAM J Comput"},{"key":"301_CR68_301","doi-asserted-by":"crossref","unstructured":"Yu SX, Shi J (2003) Multiclass spectral clustering. In: International Conference on Computer Vision, Nice","DOI":"10.1109\/ICCV.2003.1238361"},{"key":"301_CR69_301","doi-asserted-by":"crossref","unstructured":"Zhang B (2001) Generalized k\u2011harmonic means\u00a0\u2013 dynamic weighting of data in unsupervised learning. In: Proceedings of the 1st SIAM International Conference on Data Mining, Chicago","DOI":"10.1137\/1.9781611972719.6"},{"issue":"2","key":"301_CR70_301","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1023\/A:1009783824328","volume":"1","author":"T Zhang","year":"1997","unstructured":"Zhang T, Ramakrishnan R, Livny M (1997) BIRCH: A\u00a0new data clustering algorithm and its applications. J\u00a0Data Mining Knowl Discov 1(2):141\u2013182","journal-title":"J Data Mining Knowl Discov"}],"container-title":["Encyclopedia of Complexity and Systems Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-0-387-30440-3_301","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T05:44:26Z","timestamp":1739166266000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-0-387-30440-3_301"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"ISBN":["9780387758886","9780387304403"],"references-count":70,"URL":"https:\/\/doi.org\/10.1007\/978-0-387-30440-3_301","relation":{},"subject":[],"published":{"date-parts":[[2009]]}}}