2012:
A call was only made for the Prominent Paper award. The Prominent Paper award was given to:
Learning and inferring transportation routines
Lin Liao, Donald J. Patterson,
Dieter Fox, and Henry Kautz
Vol 171 (5-6), April 2007, Pages 311-331
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through an urban community, and applies it in an application that helps cognitively-impaired people use public transportation safely. The paper takes a realistic and important problem, and solves it by developing technically sophisticated, state-of-the-art AI techniques, that have applicability well beyond the domain described in the paper. This work has had a significant impact on the area of modeling and learning with dynamic Bayesian networks, both in and outside of AI. As such, the award committee unanimously believes the paper is a worthy winner of the inaugural AIJ Prominent Paper Award.