====== The Bibliography ======
===== Aggarwal =====
Charu C. Aggarwal, Jiawei Han, Jianyong Wang, and Philip S. Yu. A framework for clustering evolving data streams. In Johann Christoph Frey- tag, Peter C. Lockemann, Serge Abiteboul, Michael J. Carey, Patricia G. Selinger, and Andreas Heuer, editors, //VLDB 2003: Proceedings of 29th In- ternational Conference on Very Large Data Bases,// September 9–12, 2003, Berlin, Germany, pages 81–92, Los Altos, CA 94022, USA, 2003. Morgan Kaufmann Publishers.
===== apriori =====
Rakesh Agrawal and Ramakrishnan Srikant. Fast algorithms for mining association rules. In Jorge B. Bocca, Matthias Jarke, and Carlo Zaniolo, editors, //Proc. 20th Int. Conf. Very Large Data Bases, VLDB,// pages 487– 499. Morgan Kaufmann, 12–15 1994.
===== Al-Furaih1996 =====
Ibraheem Al-Furaih, Srinivas Aluru, Sanjay Goil, and Sanjay Ranka. Parallel construction of multidimensional binary search trees. In //ICS ’96: Proceedings of the 10th international conference on Supercomputing,// pages 205–212, New York, NY, USA, 1996. ACM Press.
===== alsabtiefficient =====
K. Alsabti, S. Ranka, and V. Singh. An efficient k-means clustering algorithm. In //Proc. First Workshop on High-Performance Data Mining,// 1998.
===== 669672 =====
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, and J ̈org Sander. Optics: ordering points to identify the clustering structure. In //SIGMOD ’99: Proceedings of the 1999 ACM SIGMOD international conference on Management of data,// pages 49–60, New York, NY, USA, 1999. ACM Press.
===== bradley98scaling =====
Paul S. Bradley, Usama M. Fayyad, and Cory Reina. Scaling clustering algorithms to large databases. In //Knowledge Discovery and Data Mining,// pages 9–15, 1998.
===== DBSCAN =====
Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu. A density-based algorithm for discovering clusters in large spatial databases with noise. In //KDD//, pages 226–231, 1996.
===== ester =====
Martin Ester and Joerg Sander. //Knowledge Discovery in Databases.// Springer Verlag, Heidelberg, 2000.
===== han =====
Micheline Kamber Jiawei Han. Data Mining: //Concepts an Techniques.// Morgan Kaufmann, 2000.
===== kanungo-efficient =====
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine Pi- atko, Ruth Silverman, and Angela Y. Wu. An efficient k-means clustering algorithm: Analysis and implementation. //IEEE Transactions on Pattern Analysis ans Machine Intelligence,// 24(7), 2002.
===== ng94efficient =====
R. T. Ng and J. Han. Efficient and effective clustering methods for spatial data mining. In Jorgeesh Bocca, Matthias Jarke, and Carlo Zaniolo, editors, //20th International Conference on Very Large Data Bases,// September 12– 15, 1994, Santiago, Chile proceedings, pages 144–155, Los Altos, CA 94022, USA, 1994. Morgan Kaufmann Publishers. CLARANS.
===== Bradley =====
Raghu Ramakrishnan Ramakrishnan Srikant Paul Bradley, Johannes Gehrke. Scaling mining algorithms to large databases. //Communications of the ACM,// 45(8):38–43, August 2002.
===== stoettinger =====
Klaus Stottinger. Kombiniertes data mining - effiziente generierung von hilfsinformationen während des clustering. Master’s thesis, Institut für Wirtschaftsinformatik, Abteilung Data & Knowledge Engineering, 2004.
===== Frawley =====
C. J. Matheus W. J. Frawley, G. Piatetsky-Shapiro. Knowledge discovery in databases: An overview. In W. J. Frawley G. Piatetsky-Shapiro, editor, //Knowledge Discovery in Databases//, pages 1–27. AAAI Press / The MIT Press, 1991.
===== zhang96birch =====
Tian Zhang, Raghu Ramakrishnan, and Miron Livny. BIRCH: an efficient data clustering method for very large databases. In //Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data,// Montreal, Quebec, Canada, June 4-6, 1996, pages 103–114, 1996.