A significant remaining challenge for existing recommender systems is that users may not trust either inaccurate recommendation or lack of explanation. Thus, it becomes critical to embrace a trustworthy system. This survey provides systematic summary three categories issues in systems: social-aware systems, which leverage users’ social relationships; robust filter untruthful information, noises...

Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about...

Recommender systems in a travel guide suggest touristic sites a user may like. Typically, people are more willing to trust recommendations from people they know. We present a trust-based recommendation service for a mobile tourist guide that uses the notion of directly and indirectly trusted peers. The recommendations combine information about the peers ratings on sights, interpersonal trust an...

With the continuous growth of the Internet and the progress of electronic commerce the issues of product recommendation and privacy protection are becoming increasingly important. Recommender Systems aim to solve the information overload problem by providing accurate recommendations of items to users. Collaborative filtering is considered the most widely used recommendation method for providing...

Recommender systems generate responses and suggest items in the required domain. This paper proposes a domain independent trust based recommender system where personalized recommendations can be generated for any domain known to the recommenders. In this recommender system, there exists a web of trust which is formed on the basis of trust among agents in application domain. Here each user captu...

In everyday life, we rely on recommendations from others to choose from various available options. While taking recommendations, people prefer recommendations from friends as they trust them to be their well wishers. This trust is referred to as friendship trust. A trust based recommender system where opinions are taken from trust worthy acquaintances to get personalized responses is proposed i...