An Event Distribution Platform for Recommending Cultural Activities

Today, people have limited leisure time which they want to fill in according to their interests. At the same time, cultural organisations offer an enormous amount of activities via their websites. This scarcity of time and the abundance of cultural events reinforce the necessity of recommender systems that assist end-users in discovering events which they are likely to enjoy. However, traditional recommender systems can not cope with event-specific restrictions such as the availability, time and location of cultural activities. Moreover, aggregating the events, collecting consistent metadata, and enriching these metadata with cross-domain knowledge pose additional challenges for the conventional distribution and recommender systems. In this paper, we show how personalised recommendation, content-based filtering, and distribution of events can be enabled by the enrichment of events metadata via open linked data sets available on the web of data. For consistency across several events providers, we propose an event model using an RDF/OWL representation of the EventsML-G2 standard. Integrating these various functionalities as an extendable bus architecture provides an open, userfriendly event distribution platform that offers the end-user a tool to access useful event information that goes beyond basic information retrieval.