recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. user similarity measurement plays an important role in collaborative filtering based recommender systems. in order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

Recommender systems are used extensively now-a-days for various web-sites such as for providing products suggestions based on customers’ purchase history and searched product keywords. Current recommendation system approaches lack of a high degree of stability. Diversification of prediction is also important feature of recommender system. Having displayed same set of results every time may incr...

In recent years, studies have focused on the development of recommender systems that consider measures that go beyond simply the accuracy of the system. One such measure, serendipity, is de ned as a measure that indicates how the recommender system can nd unexpected and useful items for users. We have previously proposed a fusion-based recommender system as a serendipity-oriented recommender sy...

A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management. Various recommender system techniques have been proposed since the mid-1990s, and many sorts of recommender system software have been developed recently for a variety of applications. Res...

A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering). Recommender systems have been a useful tool to recomm...

Virtual representatives are increasingly used in recommender systems to guide users and add conversational aspects. However, the impacts of virtual representatives on users’ evaluations of the recommender system have not been investigated. This study specifically examined the influence of virtual representatives’ anthropomorphism cues on system users’ perceptions of system credibility and likin...