Integrating clustering data mining into the multidimensional modeling of data warehouses with UML profiles

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4654 LNCS, Issue , 2007, Pages 199-208

  Zubcoff, Jose ^a   Pardillo, Jesús ^a   Trujillo, Juan ^a  

^a UNIVERSITY OF ALICANTE   (Spain)

Author keywords

Clustering; Conceptual modeling; Data mining; Data warehouse; KDD; Multidimensional modeling; Uml extension

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTER SIMULATION; DATA MINING; DATA STRUCTURES; MARKUP LANGUAGES;

CONCEPTUAL MODELING; MULTIDIMENSIONAL MODELING; UML; UML EXTENSION;

DATA WAREHOUSES;

EID: 38049029720     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74553-2_18     Document Type: Conference Paper

References (15)

1. Jain, A.K., Murty, M.N., Flynn, P.J.: Data Clustering: A Review. ACM Comput. Surv. 31(3), 264-323 (1999)
2. Frawley, W.J., Piatetsky-Shapiro, G., Matheus, C.J.: Knowledge Discovery in Databases: An Overview. In: Knowledge Discovery in Databases, pp. 1-30. AAAI/MIT Press (1991)
3. Inmon, W.H.: Building the Data Warehouse, 2nd edn. John Wiley & Sons, Inc., New York, NY, USA (1996)
4. Object Management Group: Unified Modeling Language (UML), version 2.1.1. (February 2007) http://www.omg.org/technology/documents/formal/uml.htm
5. Luján-Mora, S., Trujillo, J., Song, I.-Y.: A UML profile for multidimensional modeling in data warehouses. Data Knowl. Eng. 59(3), 725-769 (2006)
6. Zubcoff, J.J., Trujillo, J.: Extending the UML for Designing Association Rule Mining Models for Data Warehouses. In: Tjoa, A.M., Trujillo, J. (eds.) DaWaK 2005. LNCS, vol. 3589, pp. 11-21. Springer, Heidelberg (2005)
7. Zubcoff, J., Trujillo, J.: A UML 2.0 profile to design Association Rule mining models in the multidimensional conceptual modeling of data warehouses. Data Knowl. Eng. (In Press, 2006), doi: 10.1016/j.datak.2006.10.007
8. Zubcoff, J.J., Trujillo, J.: Conceptual modeling for classification mining in data warehouses. In: Tjoa, A.M., Trujillo, J. (eds.) DaWaK 2006. LNCS, vol. 4081, pp. 566-575. Springer, Heidelberg (2006)
9. Rasmussen, E.M.: Clustering Algorithms. Information Retrieval: Data Structures & Algorithms, 419-442 (1992)
10. Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs (1988)
11. Object Management Group: Object Constraint Language (OCL), version 2.0. (May 2006), http://www.omg.org/technology/documents/formal/ocl.htm
12. Object Management Group: Common Warehouse Metamodel (CWM), version 1.1 (March 2003), http://www.omg.org/technology/documents/formal/cwm.htm
13. Data Mining Group: Predictive Model Markup Language (PMML), version 3.1 (Visited April 2007), http://www.dmg.org/pmml-v3-1.html
14. Rizzi, S., Bertino, E., Catania, B., Golfarelli, M., Halkidi, M., Terrovitis, M., Vassiliadis, P., Vazirgiannis, M., Vrachnos, E.: Towards a Logical Model for Patterns. In: Song, I.-Y., Liddle, S.W., Ling, T.-W., Scheuermann, P. (eds.) ER 2003. LNCS, vol. 2813, pp. 77-90. Springer, Heidelberg (2003)
15. Rizzi, S.: UML-Based Conceptual Modeling of Pattern-Bases. In: PaRMa (2004)