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Introduction According to basic hypermedia model nodes and links constitute the hypermedia network which is a directed graph. Depending on the target task domain and scope of a hypermedia system, this simple structure could be inadequate for navigation, orientation and comprehension of accessed information. Structuring hyperspace beyond simple graphs can affect directed and undirected navigation, enhance orientation and help users to associate and thus comprehend better hypermedia information (Rivlin et all, 1994), (Botafogo et all, 1991). Hierarchical, Aggregations, Sets, Semantic nets, Petri Nets, Higraphs are structures that have been proposed for enhancing the basic hypermedia structure.
Hierarchical structures is the most widely used structure and it is the only can be found in first and second generation hypermedia systems (Conclin, 1987). Nodes are organised in hierarchical trees and thus providing the user with a set of semi-explicit links. The purpose of these organisational links is to provide users with a good knowledge of the structure of hypermedia information, and provide fast access to a subset of the hyperspace. With cross reference links still exist, hierarchical structures can provide a simple and quite efficient solution to loosely structure problem especially in tasks like writing and reading.
Aggregation is an operation that clusters related nodes and forms a higher-level object. This object can be treated as a single node. Some hypermedia provide the ability to have except single nodes, aggregation purpose nodes (Casanova, 1991). The use of aggregation structures can help users by providing abstractions about hypermedia information. Using information abstractions hypermedia can provide users with the right detail of information according to their goals. For example in a Hypermedia application about European geography, a user who has little interest in East European countries can see Western European countries in detail and all East European countries represented by a single aggregation node.
The use of semantic nets is related with the addition of artificial intelligent capabilities to hypertext systems (Diaper, Rada, 1991). According to this structure methodology nodes and links of hypermedia may be viewed as a semantic network. A link supply meaning to the pair of node it connects and a node can obtain different contents when participates in relations with different meaning. Mechanisms like spreading activation or analogical inheritance may be used for inferencing information from the hypermedia network.
The Petri net model is a generalization of traditional directed graph models. It permits development of browsing and authoring systems that can incorporate the analytical techniques that have been developed for Petri nets and also incorporate the user interface designs that have been developed for hypermedia systems. The Petri net base also permits powerful specification of how the hypertext is to be browsed. New abilities include synchronization of simultaneous traversals of separate paths through a hypertext as well as of security/access control considerations into a hypertext (specifying nodes that can be proven accessible only to certain classes of browsers). The most well known hypertext system based on Petri Nets is alpha-Trellis.