Logic has proved over centuries to be a very powerful modelling and reasoning tool, providing a degree of formality and correctness that can be very useful for manipulating information objects. Some logical models are able to represent, within a uniform framework, various features of information systems, such as hypermedia links, multimedia content, and users knowledge. Finally, logic makes it possible to reason about a model and its properties. This latter possibility is becoming increasingly important since conventional evaluation methods, although good indicators of the effectiveness of retrieval tools, often give results which cannot be predicted, or satisfactorily explained. However, logic by itself is not sufficient.
Uncertainty plays a very important role in the representation, access, and retrieval of information.
For example, the extraction of index terms or any content representation from a document or a query to represent the document or the query information content is a highly uncertain process. The data describing the redness of a red object present in a picture stored in a multimedia database is subject to a certain degree of uncertainty too. Therefore, in determining the relevance of a document to a query the truth value or the validity of a logical formula relating the two is not enough. It is necessary to take into account the uncertainty inherent in such a formulation. We are particularly interested in experiences dealing with unstructured or poorly structured information.