SWALE Project
There is a strong argument that the user's perspective has to be taken into account to ensure that the Semantic Web can improve the way computers and people work together. Personalization technologies for the Semantic Web are needed to deal with user diversity. User-adaptive systems for the Semantic Web need approaches for user modeling that work, unlike traditional approaches, under the open-world assumption. SWALE is a joint research project that investigates issues of knowledge, content and adaptation alignment between students and instructors in the context of the application of Sematic Web technologies and standard into adaptive learning systems.
OWL-OLM is a result of the ongoing research as part of the SWALE project. OWL-OLM is a novel framework for eliciting a user's conceptualization based on an ontology-driven dialog is presented here. It has been integrated in an RDF/OWL-based adaptive semantic-web software architecture for learning content management. The figure above shows the architecture of the system including the OWL-OLM Dialog and the relation to the various information models used in the system.
The personalized resource recommender is the latest additoin to the OntoAIMS system. This part uses the user's conceptualization aquired using the OWL-OLM dialog and combines this information of the user model with existing search technologies to recommend distributed resources. The figure above shows the integrated design of OntoAIMS which also contains the resource recommender. A request for relavant resources is processed using an integrated search engine, for which Lucene is used along with search engines which provide an API, such as Yahoo and Google.
Refer to the list of publications where we illustrate the implemented framework with an application scenario to deal with the cold start problem and to enable tailoring the system's behavior to the needs of each individual user.
This website also contains a demo of the system, consisting of the OntoAIMS system with integrated OWL-OLM and personalized resource recommender.
