Pattern-oriented software architecture: a system of patterns
Pattern-oriented software architecture: a system of patterns
UML toolkit
The entity-relationship model—toward a unified view of data
ACM Transactions on Database Systems (TODS) - Special issue: papers from the international conference on very large data bases: September 22–24, 1975, Framingham, MA
GeoFrame-T: a temporal conceptual framework for data modeling
Proceedings of the 9th ACM international symposium on Advances in geographic information systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A survey of data mining and knowledge discovery software tools
ACM SIGKDD Explorations Newsletter
| Hi-index | 0.00 |
Little support has been offered by geographic information systems (GIS) suppliers to reduce the complexity of geographic database (GDB) design. Design specialists [1] suggest that naive designers try to reuse at least parts of already existent, successful database schemes to reduce the effort that has to be invested in new projects. This so-called analysis patterns approach [2], [3] has a widespread acceptance in the area of software engineering. Although very promising, the use of analysis patterns in GDB design is yet very restrict. The main problem is the lack of a well known as well as globally accepted set of patterns for database design. This paper proposes the identification of analysis patterns on the basis of the Process of Knowledge Discovery in Databases (KDD). KDD supports the processing of a huge volume of database schemas and can help reducing the dependency on the subjective analysis of human specialists.