Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Utility or preference elicitation is a critical component in many recommender and decision support systems. However, most frameworks for elicitation assume a predefined set of fe...
Studies have shown that users have great difficulty specifying their security and privacy policies in a variety of application domains. While machine learning techniques have succ...
Patrick Gage Kelley, Paul Hankes Drielsma, Norman ...
Longitudinal studies of human-virtual agent interaction are expensive and time consuming to conduct. We present a new concept and tool for conducting such studies—the virtual la...
In this paper we present a trace-driven framework capable of building realistic mobility models for the simulation studies of mobile systems. With the goal of realism, this framew...
Jungkeun Yoon, Brian D. Noble, Mingyan Liu, Minkyo...