Knowledge Discovery: From Uncertainty to Ambiguity and Back

Knowledge Discovery in Databases is concerned with the development of methods and techniques for making sense of data. Its aim is to model the shapes of distributions and to discover patterns. During the knowledge acquisition process choices are made. Uncertainty and ambiguity hinder the process and “poor” choices cannot be avoided. Uncertainty corresponds to situations in which the choices are unclear and/or their consequences difficult to measure. Ambiguity arises from the lack of context, there is not sufficient information to assure the success of the choice, thus causing confusion. And decision making is hampered by perceptions of uncertainty and ambiguity.