A Survey on Pattern Application Domains and Pattern Management Approaches

Data intensive applications produce complex information that is posing requirements for novel Database Management Systems (DBMSs). Such information is characterized by its huge volume of data and by its diversity and complexity, since the data processing methods such as pattern recognition, data mining and knowledge extraction result in knowledge artifacts like clusters, association rules, decision trees and others. These artifacts that we call patterns need to be stored and retrieved efficiently. In order to accomplish this we have to express them within a formalism and a language. In this report we review the concept of patterns and their applicability in several research domains related with the proposed work and we define the knowledge domain related with the PANDA project. It is important to interrelate these domains in order to be able to define the problem in comprehensive and complete way and come up with requirements on how a management system for patterns should be. We examine the different types of patterns that are extracted from a data set, in order to gather the necessary requirements for the definition of a pattern model. This model constitutes the heart of the Pattern Base Management System that will be designed.