MUSE: A Multidimensional Semantic Environment for Adaptive Hypermedia Systems

shared ontologies and reasoning strategies (generated by the framework and semantically represented), which can be accessed and re-used by other applications. This paper proposes a semantic framework built on multidimensional ontological planes for the design of adaptive systems. The core of the framework is composed by three matrices whose different planes contain the ontological representation of different types of knowledge. On these planes we represent user features, her actions, context, device, content domain, adaptation goals and methods. The join between planes allows us to represent semantic rules for inferring new user features and to define adaptation strategies. We exploit OWL (Ontology Web Language) to represent taxonomic knowledge and SWRL (Semantic Web Rule Language) for rules. The framework presents a new approach to build adaptive hypermedia systems that support interoperability. In particular the framework manages two types of adaptation knowledge: i)knowledge regarding which features of the system have to be adapted and which dimensions (user, context, device, etc.) have to be taken into account to perform adaptation; ii)knowledge regarding adaptation strategies and rules for relating user features to other user features, extending the user model and inferring new knowledge from the available one. We represent (i) the declarative descriptions of adaptve system dimensions with ontologies expressed in a standard semantic markup language for the Semantic Web, OWL, and (ii) the inference rules with SWRL, a proposal for a semantic rule language.