Table of Contents
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.
