Imprecise Meanings as a Cause of Uncertainty in Medical Knowledge-Based Systems

Abstract

There has been a considerable amount of work on uncertainty in knowledge-based systems. This work has generally been concerned with uncertainty arising from the strength of inferences and the weighting of evidence. In this paper, we discuss another type of uncertainty: that which is due to imprecision in the underlying primitives used to represent the knowledge of the system. In particular, a given word may denote many similar but not identical entities. Such words are said to be lexically imprecise. Lexical imprecision has caused widespread problems in many areas. Unless this phenomenon is recognized and appropriately handled, it can degrade the performance of knowledge-based systems. In particular, it can lead to difficulties with the user interface, and with the inferencing processes of these systems. Some techniques are suggested for coping with this phenomenon.