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Robert Andrews
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Survey and critique of techniques for extracting rules from trained artificial neural networks
R Andrews, J Diederich, AB Tickle
Knowledge-based systems 8 (6), 373-389, 1995
17091995
The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks
AB Tickle, R Andrews, M Golea, J Diederich
IEEE Transactions on Neural Networks 9 (6), 1057-1068, 1998
5921998
Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs
S Suriadi, R Andrews, AHM ter Hofstede, MT Wynn
Information systems 64, 132-150, 2017
2762017
Process mining for healthcare: Characteristics and challenges
Journal of Biomedical Informatics 127, 103994, 2022
1532022
Rule extraction from a constrained error back propagation MLP
R Andrews, S Geva
Australian Conference on Neural Networks, Brisbane, Queensland, 9-12, 1994
851994
Quality-informed semi-automated event log generation for process mining
R Andrews, CGJ van Dun, MT Wynn, W Kratsch, MKE Röglinger, ...
Decision Support Systems 132, 113265, 2020
782020
Rule extraction from local cluster neural nets
R Andrews, S Geva
Neurocomputing 47 (1-4), 1-20, 2002
612002
Inserting and extracting knowledge from constrained error back-propagation networks.
R Andrews
Proceedings of the 6th Australian Conference on Neural Networks, 1995
551995
RULEX & CEBP Networks as the Basis for a Rule Refinement System
R Andrews, S Geva
Hybrid problems, hybrid solutions 27, 1, 1995
541995
Leveraging data quality to better prepare for process mining: an approach illustrated through analysing road trauma pre-hospital retrieval and transport processes in Queensland
R Andrews, MT Wynn, K Vallmuur, AHM Ter Hofstede, E Bosley, M Elcock, ...
International journal of environmental research and public health 16 (7), 1138, 2019
522019
A case study lens on process mining in practice
F Emamjome, R Andrews, AHM ter Hofstede
On the Move to Meaningful Internet Systems: OTM 2019 Conferences …, 2019
482019
Detection and interactive repair of event ordering imperfection in process logs
PM Dixit, S Suriadi, R Andrews, MT Wynn, AHM ter Hofstede, JCAM Buijs, ...
Advanced Information Systems Engineering: 30th International Conference …, 2018
462018
Lessons from past, current issues, and future research directions in extracting the knowledge embedded in artificial neural networks
AB Tickle, F Maire, G Bologna, R Andrews, J Diederich
Hybrid neural systems, 226-239, 2000
342000
Towards event log querying for data quality: Let’s start with detecting log imperfections
R Andrews, S Suriadi, C Ouyang, E Poppe
On the Move to Meaningful Internet Systems. OTM 2018 Conferences …, 2018
332018
Enhancing event log quality: Detecting and quantifying timestamp imperfections
DA Fischer, K Goel, R Andrews, CGJ van Dun, MT Wynn, M Röglinger
Business Process Management: 18th International Conference, BPM 2020 …, 2020
312020
Rules and local function networks
R Andrews, S Geva
Proceedings of the Workshop on Rule Extraction From Trained Artificial …, 1996
291996
Rule extraction from trained artificial neural networks
AB Tickle
Neural network analysis, architectures and applications, 61-99, 1997
281997
An evaluation and comparison of techniques for extracting and refining rules from artificial neural networks
R Andrews, R Cable, J Diederich, S Geva, M Golea, R Hayward, ...
QUT NRC (February 1996), 1996
281996
Semi-supervised log pattern detection and exploration using event concurrence and contextual information
X Lu, D Fahland, R Andrews, S Suriadi, MT Wynn, AHM ter Hofstede, ...
On the Move to Meaningful Internet Systems. OTM 2017 Conferences …, 2017
272017
Improving patient flows at St. Andrew’s War Memorial Hospital’s emergency department through process mining
R Andrews, S Suriadi, M Wynn, AHM ter Hofstede, S Rothwell
Business Process Management Cases: Digital Innovation and Business …, 2018
262018
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Articles 1–20