Riding the wave of smart disclosure initiatives and new privacy-protection regulations, the
Personal Cloud paradigm is emerging through a myriad of solutions offered to users to let …

In order to receive efficient personalized recommendation, users have to provide personal
information to service providers. However, in this process, personal private data are in an …

Recommender systems have become an integral part of many social networks and extract
knowledge from a user's personal and sensitive data both explicitly, with the user's …

User profiling is the process of collecting information about a user in order to construct their
profile. The information in a user profile may include various attributes of a user such as …

Information overload is a phenomenon of our days due to the unprecedented penetration of
information and communication technologies (ICT) in our daily lives. As a result, people …

With the rapid development of network technology and entertainment creation, the types of
movies have become more and more diverse, which makes users wonder how to choose …

Recommender systems have become extremely common in recent years, and are applied in
a variety of domains. Existing recommender systems exhibit two major limitations:(1) Privacy …

Recommender systems have proven to be an effective technique to deal with information
overload and mislead problems by helping users get useful and valuable information or …

Probabilistic matrix factorization (PMF) plays a crucial role in recommendation systems. It
requires a large amount of user data (such as user shopping records and movie ratings) to …

Recently, item-based collaborative filtering has attracted a lot of attention. It recommends to
users new items which may be of interests to them, based on their reported historical data …