Recommender Systems require specific datasets to evaluate their approach. They do not require the same information: descriptions of users or items or users interactions may be necessary, which is not gathered in today datasets. In this paper, we provide a dataset containing reviews from users on items, trust values between users, items category, categories hierarchy and users expertise on categ...

In this thesis, we build an agent-based framework to model trust-based interaction among people in a social network. We assume that trust is one person’s expectancy that another person will behave in a way that a good outcome for both people is achieved. The social network is represented by a weighted graph in which the nodes are the agents and the links reflect the strength of trust relationsh...

Peer production, a new mode of production, is gradually shifting the traditional, capital-intensive wealth production to a model which heavily depends on information creating and sharing. More and more online users are relying on this type of services such as news, articles, bookmarks, and various user-generated contents around World Wide Web. However, the quality and the veracity of peers’ con...

Trust is required in file sharing peer-to-peer (P2P) systems to achieve better cooperation among peers and reduce malicious uploads. In reputation-based P2P systems, reputation is used to build trust among peers based on their past transactions and feedbacks from other peers. In these systems, reputable peers will usually be selected to upload requested files, decreasing significantly malicious...

In a growing number of domains, recommender systems support users’ decision making processes in finding entities (such as book, movies, or newspaper articles) matching their individual preferences. Individual preferences vary extensively thus hampering the creation of good recommender systems. Additionally, the relevance of items to users depends on a plethora of criteria. Such relevance criter...

Agent-based recommender systems have been widely employed in the last years to provide informative suggestions to users, showing the advantage of exploiting components like beliefs, goals and trust in the recommendation computation. However, many real-world recommendation scenarios, like the traffic or the health ones, require to represent and reason about spatial and temporal knowledge, consid...

There have been various definitions, representations and derivations of trust in the context of recommender systems. This article presents a recommender predictive model based on collaborative filtering techniques that incorporate a fuzzy-driven quantifier, which includes two upmost relevant social phenomena parameters to address the vagueness inherent in the assessment of trust in social netwo...

Trust has been explored by many researchers in the past as a solution for assisting the process of recommendation production. In this work we are examining the feasibility of building networks of trusted users using the existing evidence that would be provided by a standard recommender system. As there is lack of models today that could help in finding the relationship between trust and similar...

Trust has been shown as a crucial factor for the adoption of new technologies. Surprisingly, trust literature offers very little guidance for systematically integrating the vast amount of insights from behavioral research on trust into the development of computing systems. The aim of this article is to translate results from behavioral sciences into software requirement patterns that address us...