The document presents a hybrid event recommendation approach that combines collaborative filtering and content-based filtering using linked data and detecting user interests. It models events as entities in an RDF graph and computes similarity based on related entities. It uses LDA to detect user interests from their attended event distributions. The hybrid approach ranks recommendations based on content and collaborative filtering. An evaluation on real world event data found the approach outperforms other methods, and social and interest factors highly influence recommendations.