Modeling human daily preferences through a context-aware web-mapping system using semantic technologies

In this paper, a novel geosocial networking service called “G-SPLIS” (Geosocial Semantic Personalized Location Information System) is presented. The paper provides a methodology to design, implement and share in a formal way human daily preferences regarding points of interest (POIs) and POI owners’ group targeted offering policies, via user-defined preferences and policy rules. By adding rules at run time users have more flexibility and they do not rely on the pre-determined application’s methods to get personalized information. Furthermore, G-SPLIS provides a large knowledge base for other systems in the web, because rules are easily sharable. To achieve the above, the presented system is compatible with Semantic Web standards such as the schema.org ontology and uses RuleML for rules that define regular users’ preferences and POI owner’s group-targeted offers. Finally, it combines at run-time the above to match user context with related information and visualizes personalized information.