A Framework for Context-Aware Service Recommendation
Accomplishing well-timed service recommendation involves context-awareness and calculation of similarity between services. An ontology-based context model, in which RDF reification is used to describe temporal characteristics, is presented in this paper. Accordingly, ontology-based context reasoning which cooperates with duration reasoning is adopted to derive high-level contexts from raw data. SAW algorithm is also improved in the capability of dealing with semantics, and with the advanced algorithm, an appropriate service can be selected from service depository as the proposal to the user. Finally, the architecture of the proposed framework is explained.