Abstract
Information retrieval of a conventional fuzzy detabase is executed on the base of equality of attribute values of stored data and the one of a retrieval condition. But, when the attribute values are very fuzzy, the information retrieval on the base of "equality" often gives us unreasonable results in comparison with our ordinary common sense. In order to overcome the difficulty of the information retrieval for very large fuzzy data, the authors express the fuzzy attribute value of stored data and a retrieval condition in a label and its membership function, and formulate the new method of fuzzy information retrieval by defining the satisfaction grade, that estimates how the attributes of stored data satisfy the one of a fuzzy retrieval condition. By example of paintings, the authors discuss usability and effectiveness of the information retrieval formulated here.
