An adaptive recommendation service seeks to adapt to its users, providing increasingly personalized recommendations over time. In this paper we introduce the \Fab" adaptive W...
Recommendation systems can be attacked in various ways, and the ultimate attack form is reached with a sybil attack, where the attacker creates a potentially unlimited number of s...
Haifeng Yu, Chenwei Shi, Michael Kaminsky, Phillip...
Recommender systems perform much better on users for which they have more information. This gives rise to a problem of satisfying users new to a system. The problem is even more a...
Web-based applications with a large variety of users suffer from the inability to satisfy heterogeneous needs. A remedy for the negative effects of the traditional "one-size-...
Paolo Buono, Maria Francesca Costabile, Stefano Gu...
The increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for knowledge discovery in transportation systems. A particular...
Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao,...