ABSTRACT
In many multimedia data mining applications, it is often required to make a decision in an imprecise and uncertain environment. For example, in the application of mining an image database with a query image of green trees, given an image in the database that is about a pond with a bank of earth and a few green bushes, is this image considered as a match to the query? Certainly this image is not a perfect match to the query, but, on the other hand, it is also not an absolute mismatch to the query. Problems like this example, as well as many others, have intrinsic imprecision and uncertainty that cannot be neglected in decision making. Traditional intelligent systems fail to solve such problems, as they attempt to use Hard Computing techniques. In contrast, a Soft Computing methodology implies cooperative activities rather than autonomous ones, resulting in new computing paradigms such as fuzzy logic, neural networks, and evolutionary computation. Consequently, soft computing opens up a new research direction for problem solving that is difficult to achieve using traditional hard computing approaches.
