A Context-awareness Based Dynamic Personalized Hierarchical Ontology Modeling Approach

This paper proposes a new approach to construct an efficient and dynamic updated ontology model. In order to capture the implicit context information and to implement the personalized scalability demands of context model for different users, this paper proposes a new approach to construct a context-awareness based dynamic personalized hierarchical ontology model which divides the ontology into 2 layers: the first layer (general context-aware ontology) is used to capture the most essential conceptual entities in the context-aware computing environment, and the second layer (personalized ontology) is used to capture the individual user's preference by considering the domain ontology, knowledge structure, the term co-occurrence frequency and the Active Degree of each device. An algorithm of Domain Classification Algorithm is used and an Improved Concept Identification Algorithm is proposed in this research. The simulation results show that the time overhead of the hierarchical ontology model is low and it provides the users with results that more accurately satisfy their specific goal and intent.