Generalization
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Generalization is a foundational element of logic and human reasoning. It is the essential basis of all valid deductive inference. The concept of generalization has broad application in many related disciplines, sometimes having a specialized context-specific meaning.
For any two related concepts, A and B; A is considered a generalization of concept B if and only if:
- every instance of concept B is also an instance of concept A; and
- there are instances of concept A which are not instances of concept B.
For instance, animal is a generalization of bird because every bird is an animal, and there are animals which are not birds (dogs, for instance). (See also: specialization).
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[edit] Hypernym and hyponym
This kind of generalization versus specialization (or particularization) is reflected in either of the contrasting words of the word pair hypernym and hyponym. A hypernym as a generic stands for a class or group of equally-ranked items, such as tree does for beech and oak; or ship for cruiser and steamer. Whereas a hyponym is one of the items included in the generic, such as lily and daisy are included in flower, and bird and fish in animal. A hypernym is superordinate to a hyponym, and a hyponym is subordinate to hypernym.
[edit] Generalization of geo-spatial data
Generalization has a long history in cartography as an art of creating maps for different scale and purpose.
As GIS came up in the last century and the demand for producing maps automatically increased automated generalization became an important issue for National Mapping Agencies (NMAs) and other data providers. Thereby automated generalization describes the automated extraction of data (becoming then information) regarding purpose and scale. Different researchers invented conceptual models for automated generalization:
- Gruenreich model
- Brassel & Weibel model
- McMaster & Shea model
Besides these established model, different views on automated generalization have been established. The representation-oriented view and the process-oriented view. The first view focuses on the representation of data on different scales, which is related to the field of Multi-Representation Databases (MRDB). The latter view focuses on the process of generalization.
In the context of creating databases on different scales additionally it can be distinguished between the ladder and the star-approach. The ladder-approach is a stepwise generalization, in which each derived dataset is based on the other database of the next larger scale. The star-approach describes the derived data on all scales is based on a single (large-scale) data base.
[edit] Operators in automated generalization
Automated generalization had always to compete with manual cartographers, therefore the manual generalization process was studied intensively. These studies resulted early in different generalization operators. By now there is no clear classification of operators available and it is doubtable, if a comprehensive classification will evolve in future.
[edit] Reference
McMaster, R.B. and Shea, K.S. 1992. Generalization in Digital Cartography. Washington, DC: Association of American Geographers.
[edit] See also
- Generic
- inheritance (object-oriented programming),
- faulty generalization
- hasty generalization
- -onymde:Generalisierung
et:Üldisus es:Generalización he:הכללה (מתמטיקה) sr:Генерализација sv:Generalisering
