A concept hierarchy defines a sequence of mappings from a set of – low-level concepts to higher-level, more general concepts. Consider a concept hierarchy for the dimension location. City values for the locution include – Vancouver, Toronto, New York, and Chicago. Each city, however, can be mapped to the country to which it belongs, such as Canada or the USA. These mappings from a concept hierarchy for the dimension location, mapping a set of. low, level concepts to higher-level, more general concepts. The concept hierarchy described above is illustrated in fig. 2.8.
A concept hierarchy that is a total or partial order among attributes in a database schema is called a schema hierarchy. Concept hierarchies that are common to many applications may be predefined in the data mining system. Data mining systems should provide users With the flexibility to tailor predefined hierarchies according to their particular needs. Concept hierarchy may also be defined by discretizing or grouping values for a given dimension or attribute, resulting in a set grouping hierarchy. A total or partial order can be defined among groups of values. There may be more than one concept. hierarchy for a given attribute or dimension based on different user viewpoints.
Concept hierarchy. may be provided manually by system users, domain experts, or knowledge engineers, or may be automatically generated based on ..statistical analysis of the data distribution. Concept-hierarchies allow data to – be handled at varying levels of abstraction.
Manual definition of concept hierarchy can be a tedious and time-consuming task for a user domain fortunately several discretization methods can be used to automatically generate or dynamically refine concept hierarchy for the numerical attribute. Furthermore, many hierarchies for categorical attributes are implicit within the database schema and can be automatically defined at the schema definition level.