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A Framework to Provide Customized Reuse of Open Corpus Content for Adaptive Systems

One of the main services that Adaptive Systems offer to their users is the provision of content that is tailored to individual user's needs. Some Adaptive Systems use a closed corpus content that has been prepared for them a priori, hence, they accept only a narrow field of content. Furthermore, the content is tightly coupled with other parts of the system, which also hinders its re-usability. To address these limitations, recent systems started to make use of open Web content to provide a wider variety of content. Previous approaches have attempted to harness the information available on the web by providing adaptive systems with customizable information objects. Since adaptive systems are evolving towards the Semantic Web and the use of ontologies, existing systems are limited by their ability to service these documents solely through keyword-based queries. In this research we propose a novel framework that extends existing content provision system, Slicepedia. Our framework uses the conceptual representation of content to segment it in a semantic manner. The framework removes unnecessary content from web pages, such as navigation bars, and then semantically reveals the structural representation of text to build a tree-like hierarchy. This tree can be traversed to obtain different levels of content granularity that facilitate content discoverability and adaptivity.