The advancement in technology accelerated and opened availability of various alternatives to make a choice in every domain. In the era of big data it is a tedious and time consuming task to evaluate the features of a large amount of information provided to make a choice. One solution to ease this overload problem is building recommender system that can process a large amount of data and support users' decision making ability. In this paper different traditional recommendation techniques, deep learning approaches for recommender system and survey of deep learning techniques on recommender system are presented. A variety of techniques have been proposed to perform recommendation, including content based, collaborative and hybrid recommenders. Due to the limitation of the traditional recommendation methods in obtaining accurate result a deep learning approach is introduced both for collaborative and content based approaches that will enable the model to learn different features of users and items automatically to improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender systems have not been fully exploited. With the help of the advantage of deep learning in modeling different types of data, deep recommender systems can better understand users' demand to further improve quality of recommendation.
General TermsRecommender system, deep learning
KeywordsRecommender system, deep learning, big data, decision making, collaborative filtering, hybrid recommender.
Shortage of medical personnel and the existence of inexperienced ones, are frequently the causes of false diagnosis, and call for a reflection on the methods of training of the later. One of the solutions might be the application of new technologies in the training of medical students, in order to counter the shortage of experts as well as training conditions which are usually inadequate (no patients available for practice). The aim of this paper is to propose a virtual patient, on which an expert can formulate pathology, and hand this patient to a learner for exercises on medical diagnostics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.