Approximation of indistinct concepts
Mingyi Zhang · International Joint Conference on Artificial Intelligence · 1989
This theory on semi-equivalence relations is an important and useful tool for investigating classification, pattern recognition, polling and inference etc. Based on it, this paper presents a new framework, in which an indistinct concept, that is one with incomplete or undetermined information about the objects, can be represented approximately. Such an approximate representation will reflect deep structures of concepts which are meaningful for the system. Clearly, the work we present here is to a great extent inspired by general discussions of knowledge engineering research. The theory developed here seems to be of interest in knowledge representation and natural language processing. From the implementation point of view, this theory can be realized by various AI techniques.