Monitoring security and trust in on-line personalised recommendation systems is now recognised as a key challenge. Noisy data, or maliciously biased data, can significantly skew the system’s output. This paper out-lines our research goals, which aim to tackle this issue along a number of lines. Game theoretic techniques are applied to determining bounds on the effect of robust-ness attacks on recommender systems. Graph theoretic techniques are used to analyse the dataset structure and identify influential users in the application user-group, for filtering purposes. A user profile database is a key component of most on– line e–commerce systems. The database stores user infor-mation such as the history of access patterns to the site, prod
Recommender systems are widely used in a variety of scenarios, including online shopping, social net...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
We address the fundamental tradeoff between privacy preservation and high-quality recommendation ste...
Abstract Despite its success, similarity-based collaborative filtering suffers from some limitations...
Collaborative filtering techniques have been successfully em-ployed in recommender systems in order ...
Recommender systems play an essential role in our digital society as they suggest products to purcha...
Abstract. Recommender systems are widely used to help deal with the problem of information overload....
This paper examines the effect of Recommender Systems in security oriented issues. Currently researc...
Trust, reputation and recommendation are key components of successful ecommerce systems. However, ec...
Nowadays, online services, like e-commerce or streaming services, provide a personalized user experi...
In pervasive/ubiquitous computing environments, interacting users may evaluate their respective trus...
Recently, recommender systems have achieved promising performances and become one of the most widely...
The modeling of Web user navigational patterns is a critical component of many Web applications such...
The recommendation systems used to form a news feed in social networks or to create recommendation l...
The recommendation systems used to form a news feed in social networks or to create recommendation l...
Recommender systems are widely used in a variety of scenarios, including online shopping, social net...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
We address the fundamental tradeoff between privacy preservation and high-quality recommendation ste...
Abstract Despite its success, similarity-based collaborative filtering suffers from some limitations...
Collaborative filtering techniques have been successfully em-ployed in recommender systems in order ...
Recommender systems play an essential role in our digital society as they suggest products to purcha...
Abstract. Recommender systems are widely used to help deal with the problem of information overload....
This paper examines the effect of Recommender Systems in security oriented issues. Currently researc...
Trust, reputation and recommendation are key components of successful ecommerce systems. However, ec...
Nowadays, online services, like e-commerce or streaming services, provide a personalized user experi...
In pervasive/ubiquitous computing environments, interacting users may evaluate their respective trus...
Recently, recommender systems have achieved promising performances and become one of the most widely...
The modeling of Web user navigational patterns is a critical component of many Web applications such...
The recommendation systems used to form a news feed in social networks or to create recommendation l...
The recommendation systems used to form a news feed in social networks or to create recommendation l...
Recommender systems are widely used in a variety of scenarios, including online shopping, social net...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
We address the fundamental tradeoff between privacy preservation and high-quality recommendation ste...