A Rule-Based Adaption Model for Ontology-Based Personalization

Various adaptive hypermedia systems have been proposed to alleviate information overload on the Web by personalising the delivery of information and resources to the user. These systems have however been afflicted with difficulties in the acquisition of an accurate user model, a limited degree of customization offered to the user as well as general lack of user control on and transparency of the systems' adaptive behavior. In this chapter, we argue that the use of rules on top on ontologies can enable adaptive functionality that is transparent and controllable for users. To this end, we present ODAS, a domain ontology for adaptive hypermedia systems, and a model for the specification of ODAS-based adaptation rules. We demonstrate the use of this model by showing how it can be instantiated within a knowledge portal to arrive at rules that exploit ODAS semantics to perform meaningful personalization.