Context-Aware Trust Aided Recommendation via Ontology and Gaussian Mixture Model in Big Data Environment

With the development of big data, the data size becomes bigger and bigger, which makes users consume enormous time to find the items that they might like from abundant options. Recommender systems are expected to help users find interested items. However, most existing recommendation methods do not take into account any additional contextual information with a reasonable complexity. This paper aims to propose a context-aware recommender system by incorporating context-aware technology into recommendation. The context-aware approach is based on ontology and Gaussian Mixture Model. The recommendation analysis is implemented by trust aided probabilistic matrix factorization approach. The evaluation shows that the proposed approach has a good effect in recommendation quality.