KNOWEL: A Hypermedia Kowledge Editor M. Vazirgiannis, A. Kalousis, M. Hatzopoulos Department of Informatics, University Campus, University of Athens, 15771, Ilisia, Athens, Greece e-mail: {michalis, grad0058, mike}@di.uoa.gr Abstract A popular approach for organising and accessing information is the hypermedia approach. One of the features that is weak in current hypermedia systems is the semantics of the nodes and links. In principle nodes are classified into categories while links represent abstract relationships among concepts. In this paper we present the implementation of parts of an object oriented data model that represents hypermedia information networks integrating semantics and multimedia information. The implementation refers to the parts of the data model that represent fuzzy knowledge in hypermedia networks. Special emphasis is put to the fuzzy features of the relationships among concepts. 1. Introduction A popular approach for organising and accessing information is the hypermedia approach. The information in such an approach uses nodes to represent the information itself and links for the interconnections among nodes. The links represent the semantic relationships among the nodes. One of the features that is weak in current hypermedia systems is the semantics of the nodes and links. Nodes are classified into concept categories while links represent abstract relationships among concepts Current proposed standards (MHEG, HYTIME) refer to structural organisation of hypermedia documents without special reference to their semantics. In general there is a lack of semantic organisation of hypermedia systems, especially as regards the semantics of links and nodes. Moreover an issue is the representation and manipulation of the uncertainty of the relationships that are represented by the links. Today it is widely accepted that an important problem in AI is the representation of common- sense knowledge. Conventional knowledge representation schemes (predicate calculus and related methods) are not well suited for representing common-sense knowledge [10]. Moreover the conventional approaches to knowledge representation (semantic networks, frames, predicate calculus and Prolog ) are based on bivalent logic. A serious shortcoming of such approaches is their inability to come to grips with the issue of uncertainty and imprecision. [11]. Fuzzy Logic provides an effective conceptual framework for dealing with the problem of knowledge representation in an environment of uncertainty and imprecision. Fuzzy logic is applied to various areas of Artificial Intelligence such as: natural language understanding [6] or abductive inference [ 2]. In this paper we present a knowledge editor that may be utilised for the task of semantics enforcement over a hypermedia network. The representation of concepts and relationships exploits fuzzy logic for modelling the uncertainty of a hypermedia network. KNOWEL is based on an Object Oriented Model [9] that represents in an integrated and uniform way all the information layers involved in a hypermedia information system (multimedia objects and presentations, nodes, links and the semantics that are embedded in the hypermedia network) 2. The data model The data model [9] that served as the theoretical framework aims at representation of hypermedia information networks. More specifically the model represents the knowledge that is included in a hypermedia information network (in terms of concepts, relationships and weights), the hypermedia network itself (in terms of nodes and links), the multimedia presentations that are embedded in the nodes (in terms of scenes, scenario, spatial and temporal compositions). There is a vertical flow of information. The information in a hypermedia information system may be classified into different layers (fig. 1.). the upper layer includes the objects that represent fuzzy knowledge (concepts, relationships,