Integration of Heterogeneous Web Services for Event-Based Social Networks

Event-based online social networks are Internet-based services that enable users to participate in real world experiences together. Event-based social networks can be created by a community of end-users based on their own interests in specific types of event and sources of event information. We propose a method to create such event-based social networks through integration of existing online information sources of events using a Semantic Web framework. In order to match people with common interests in such activities to self-organize into a social network, we integrate information from heterogeneous information sources related to event schedules, ticket purchases, and group attendance from multiple online sources. The Semantic Web framework is used to represent these heterogeneous datasets and unstructured online data is converted into ontologies. Links between event information in different sources are discovered using both the syntactic similarity and semantic similarity between ontology classes. We use an approach based on Latent Dirichlet Allocation (LDA) over the space of topics related to each event and user profiles for event recommendation. This enables the event-based social network to recommend friends based on shared interest in an event - online friendship is established after mutual attendance of the same event. We demonstrate this approach with EasyGo, a web-based mashup application which integrates information of events such as concerts, sports, theatres, as well as tickets and group purchase from multiple online sources.