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AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
15 years 7 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
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...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
RECSYS
2009
ACM
15 years 8 months ago
Preference elicitation with subjective features
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...
Craig Boutilier, Kevin Regan, Paolo Viappiani
CCS
2008
ACM
15 years 3 months ago
User-controllable learning of security and privacy policies
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 ...
ATAL
2009
Springer
15 years 8 months ago
A virtual laboratory for studying long-term relationships between humans and virtual agents
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...
Timothy W. Bickmore, Daniel Schulman
MOBISYS
2006
ACM
16 years 1 months ago
Building realistic mobility models from coarse-grained traces
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...