Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ontology-based generation of Object Oriented Bayesian Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mouna Ben Ishak, Philippe Leray and Nahla Ben Amor Exploratory network analysis of large social science questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Robert J. B. Goudie, Sach Mukherjee and Frances Griffiths Constructing a Dynamic Bayes Net Model of Academic Advising . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Joshua T. Guerin and Judy Goldsmith Context-dependent Incremental Intention Recognition through Bayesian Network Model Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 The Anh Han and Lu´ıs Moniz Pereira A decision support-system for the mediastinal staging of non-small cell lung cancer . . . . . . . . . . . . . . 83 Manuel Luque, Francisco Javier D´ıez and Carlos Disdier Using Tree Augmented Naive Bayesian Classifiers to Improve Engine Fault Models . . . . . . . . . . . . . . 91 Daniel L. Mack, Gautam Biswas, Xenofon D. Koutsoukos and Dinkar Mylaraswamy Anomaly Detection in Vessel Tracks using Bayesian networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Steven Mascaro, Kevin B. Korb and Ann E. Nicholson ABC-BN: A tool for building, maintaining and using Bayesian networks in an environmental management application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Ann E. Nicholson, Owen Woodberry, Steven Mascaro, Alicia Lucas, Adrian Moorrees and Kevin B. Korb Does Query-Based Diagnostics Work? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Parot Ratnapinda and Marek J. Druzdzel A Web-based Tool for Expert Elicitation in Distributed Teams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Carlo Spaccasassi and Lea Deleris
Program Committee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii Real-time event recognition from video via a “bag-of-activities” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Rolf Baxter, Neil M. Robertson and David Lane 9 Building a Real-Time System for High-Level Perception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Denver Dash and Long Quoc Tran Constructing Bayesian Networks for Linear Dynamic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Sander Evers and Peter J.F. Lucas