A Context-Aware Reasoning Framework with OWL for Mobile Web Information Acquisition

Abstract

As the mobile Internet era advances, using mobile devices to access web content has become more and more popular. However, users often find that mobile web content acquisition is not convenient as expected and is problematic. In this study, we devise a context-aware reasoning framework to tackle this problem. We implement a prototype system using Protégé with Jess Tab, which is a plug-in Jess module. In the proposed framework, the user profile, network and environment parameters, device information, etc. are characterized as the user context and is described in OWL format so that it can be shared, reused and applied to the reasoning engine. With Protégé, we build a user context template, which is an OWL document, and design a context updater to automatically update the context information. The web content ontology is constructed also with Protégé and is exported into OWL format so that logic inference for web page navigation can be performed automatically. Moreover, reasoning rules are defined so as to automatically infer appropriate web information for users. A pragmatic example with our prototype system shows that, with the proposed context-aware reasoning framework, a mobile user can be automatically and easily navigated to access the web page that he or she wants to browse and, therefore, can acquire the appropriate web information quickly and efficiently.