Concept map assessment for teaching computer programming J Keppens, D Hay Computer Science Education 18 (1), 31-42, 2008 | 102 | 2008 |
Knowledge based crime scenario modelling J Keppens, B Schafer Expert Systems with Applications 30 (2), 203-222, 2006 | 81 | 2006 |
On compositional modelling J Keppens, Q Shen The knowledge engineering review 16 (2), 157-200, 2001 | 66 | 2001 |
A scenario-driven decision support system for serious crime investigation Q Shen, J Keppens, C Aitken, B Schafer, M Lee Law, Probability and Risk 5 (2), 87-117, 2006 | 58 | 2006 |
A model based reasoning approach for generating plausible crime scenarios from evidence J Keppens, J Zeleznikow Proceedings of the 9th international conference on artificial intelligence …, 2003 | 54 | 2003 |
Linguistic bayesian networks for reasoning with subjective probabilities in forensic statistics J Halliwell, J Keppens, Q Shen Proceedings of the 9th international conference on artificial intelligence …, 2003 | 47 | 2003 |
Impact of receiving recorded mental health recovery narratives on quality of life in people experiencing psychosis, people experiencing other mental health problems and for … S Rennick-Egglestone, R Elliott, M Smuk, C Robinson, S Bailey, R Smith, ... Trials 21, 1-34, 2020 | 44 | 2020 |
Argument diagram extraction from evidential Bayesian networks J Keppens Artificial Intelligence and Law 20, 109-143, 2012 | 44 | 2012 |
On extracting arguments from Bayesian network representations of evidential reasoning J Keppens Proceedings of the 13th international conference on artificial intelligence …, 2011 | 30 | 2011 |
Efficient norm emergence through experiential dynamic punishment S Mahmoud, N Griffiths, J Keppens, M Luck ECAI 2012, 576-581, 2012 | 28 | 2012 |
Towards qualitative approaches to Bayesian evidential reasoning J Keppens Proceedings of the 11th international conference on artificial intelligence …, 2007 | 27 | 2007 |
Establishing norms with metanorms in distributed computational systems S Mahmoud, N Griffiths, J Keppens, A Taweel, TJM Bench-Capon, M Luck Artificial Intelligence and Law 23, 367-407, 2015 | 25 | 2015 |
DESO: Addressing volume and variety in large-scale criminal cases O Brady, R Overill, J Keppens Digital Investigation 15, 72-82, 2015 | 24 | 2015 |
Compositional Bayesian modelling for computation of evidence collection strategies J Keppens, Q Shen, C Price Applied Intelligence 35, 134-161, 2011 | 24 | 2011 |
Probabilistic abductive computation of evidence collection strategies in crime investigation J Keppens, Q Shen, B Schafer Proceedings of the 10th international conference on artificial intelligence …, 2005 | 24 | 2005 |
Children's Rights: Monitoring Issues. E Verhellen, F Spiesschaert Mys & Breesch, Coupure 120-B-9000, Gent, Belgium (950 Belgian Francs)., 1994 | 23 | 1994 |
An analysis of norm emergence in Axelrod's model S Mahmoud, N Griffiths, J Keppens, M Luck | 22 | 2010 |
Addressing the increasing volume and variety of digital evidence using an ontology O Brady, R Overill, J Keppens 2014 IEEE joint intelligence and security informatics conference, 176-183, 2014 | 21 | 2014 |
Requirements analysis: Evaluating kaos models F Almisned, J Keppens Journal of Software Engineering and Applications 3 (9), 869, 2010 | 21 | 2010 |
On the role of model-based reasoning in decision support in crime investigation J Keppens, J Zeleznikow Proceedings of the 3rd International Conference on Law and Technology, 77-83, 2002 | 19 | 2002 |