Ontology-based recommender system satisfying application requirements

Companies are increasingly recognizing the potential of the recommendation system. Various filter methods for recommendation systems have been identified in the literature. These are collaborative filtering (e.g., customers who bought product A, also product B),content-based filtering (e.g., you bought a printer, you may also need ink) or knowledge-based filtering (e.g., we know you like skirts: do you prefer the red or the blue skirt?). Two or more methods can be combined into so-called hybrid systems that try to combine the best aspects of each system. Another new trend is chatbots, as they can offer a personal and fast service to the customer. The combination of both technologies makes it easier for companies to communicate with their customers. The goal is for the customer to come back. However, current solutions do not focus on the alignment between the application view and the technical view; customers need to have a lot of expertise....