The Role of Classification in Knowledge Representation and Discovery - 1

The use of trees as knowledge representations shares some of the same problems as does the use of hierarchies:

* Rigidity. Because a tree is characterized by the relationships among entities and the citation order, the general shape of the tree--its expressiveness as a knowledge representation--is determined a priori. This means that new entities can be added, if they fit into a place in the structure but, if the new entity or new knowledge does not fit well, the entire structure must be rethought and sometimes rebuilt.

* One-way flow of information. In a hierarchy, information flows in two directions: vertically, between classes, superclasses, and subclasses, and also laterally, between sibling classes (classes sharing the same superclass). In a tree, even if it is a part/whole representation, the information flows in a vertical direction up and down. Siblings in a class may in fact be entirely different types of objects. So there are rules for species but not for differentia. Many people assume that, since Syracuse is in New York State and New York City is also in New York State, that they are similar when in fact they only share the attribute of being in the same state and little else. Syracuse may be more like some other city in another state than it is like New York City. At any rate, the tree classification is not particularly good at representing multidirectional complex relationships.

* Selective perspective. As with hierarchies, by emphasizing a certain relationship, a tree can mask, or fail to reveal, other equally interesting relationships. For instance, in the Army ranks example, the only relationship available to us is the "who commands whom" relationship. It does not touch upon the relationship of ranks when in combat, for instance, as opposed to the relationships among ranks of troops stationed at home. It does not show the distribution of men to women in the various ranks, or the distribution of ethnic or racial groups, and so on. It is completely silent on the classification of functional jobs in the Army (such as nurses, quartermasters, and so on). In other words, there are many other perspectives or lenses through which one could "know" the Army. The typology of ranks based on who commands whom is but one of them.

In summary, trees are useful for displaying information about entities and their relationships along one dimension of interest. They require fairly complete knowledge about a domain or at least about one aspect of a domain. A tree representation is good for displaying the relative placement of entities with respect to each other and their frequency at any node. On the other hand, trees are limited in how much they can represent, especially in terms of knowledge about entities within the same class. Furthermore, trees allow only partial inference.

Paradigms. A third classificatory structure is one in which entities are described by the intersection of two attributes at a time. The resulting matrix (or paradigm) reveals the presence or absence and the nature of the entity at the intersection (see Figure 5).