2009 |
19 | EE | Stijn Viaene,
Luc Lutin,
Steven De Hertogh:
Operationalised Business Intelligence: Knowledge Sharing with an Enterprise Ambition at the Amsterdam-Amstelland Police Department.
HICSS 2009: 1-10 |
2008 |
18 | EE | Jonas Poelmans,
Paul Elzinga,
Stijn Viaene,
Guido Dedene:
An Exploration into the Power of Formal Concept Analysis for Domestic Violence Analysis.
ICDM 2008: 404-416 |
2007 |
17 | EE | John Ward,
Steven De Hertogh,
Stijn Viaene:
Managing Benefits from IS/IT Investments: An Empirical Investigation into Current Practice.
HICSS 2007: 206 |
2006 |
16 | EE | Bjorn Cumps,
Stijn Viaene,
Guido Dedene,
Jacques Vandenbulcke:
An Empirical Study on Business/ICT Alignment in European Organisations.
HICSS 2006 |
15 | EE | Koen Milis,
Stijn Viaene,
Pieter M. A. Ribbers:
On How the Feasibility Study Is Influenced by an ICT Project's Main Trigger.
HICSS 2006 |
2005 |
14 | EE | Stijn Viaene,
Guido Dedene:
Cost-sensitive learning and decision making revisited.
European Journal of Operational Research 166(1): 212-220 (2005) |
13 | EE | Stijn Viaene,
Guido Dedene,
Richard A. Derrig:
Auto claim fraud detection using Bayesian learning neural networks.
Expert Syst. Appl. 29(3): 653-666 (2005) |
2004 |
12 | EE | Stijn Viaene,
Dirk Van Gheel,
Mercedes Ayuso,
Montserrat Guillen:
Cost-Sensitive Design of Claim Fraud Screens.
Industrial Conference on Data Mining 2004: 78-87 |
11 | EE | Stijn Viaene,
Richard A. Derrig,
Guido Dedene:
A Case Study of Applying Boosting Naive Bayes to Claim Fraud Diagnosis.
IEEE Trans. Knowl. Data Eng. 16(5): 612-620 (2004) |
10 | EE | Stijn Viaene,
Richard A. Derrig,
Guido Dedene:
Cost-sensitive learning and decision making for massachusetts pip claim fraud data.
Int. J. Intell. Syst. 19(12): 1197-1215 (2004) |
9 | EE | Tony Van Gestel,
Johan A. K. Suykens,
Bart Baesens,
Stijn Viaene,
Jan Vanthienen,
Guido Dedene,
Bart De Moor,
Joos Vandewalle:
Benchmarking Least Squares Support Vector Machine Classifiers.
Machine Learning 54(1): 5-32 (2004) |
2002 |
8 | EE | Stijn Viaene,
Richard A. Derrig,
Guido Dedene:
Boosting Naive Bayes for Claim Fraud Diagnosis.
DaWaK 2002: 202-211 |
7 | | Stijn Viaene,
Bart Baesens,
Guido Dedene,
Jan Vanthienen,
Dirk Van den Poel:
Proof Running Two State-Of-The-Art Pattern Recognition Techniques in the Field of Direct Marketing.
ICEIS 2002: 446-454 |
2001 |
6 | | Bart Baesens,
Rudy Setiono,
Christophe Mues,
Stijn Viaene,
Jan Vanthienen:
Building Credit-Risk Evaluation Expert Systems Using Neural Network Rule Extraction and Decision Tables.
ICIS 2001: 159-168 |
5 | | Stijn Viaene,
Bart Baesens,
Tony Van Gestel,
Johan A. K. Suykens,
Dirk Van den Poel,
Jan Vanthienen,
Bart De Moor,
Guido Dedene:
Knowledge discovery in a direct marketing case using least squares support vector machines.
Int. J. Intell. Syst. 16(9): 1023-1036 (2001) |
2000 |
4 | EE | Geert Poels,
Stijn Viaene,
Guido Dedene:
Distance Measures for Information System Reengineering.
CAiSE 2000: 387-400 |
3 | EE | Bart Baesens,
Stijn Viaene,
Jan Vanthienen,
Guido Dedene:
Wrapped Feature Selection by Means of Guided Neural Network Optimization.
ICPR 2000: 2113-2116 |
2 | EE | Bart Baesens,
Stijn Viaene,
Tony Van Gestel,
Johan A. K. Suykens,
Guido Dedene,
Bart De Moor,
Jan Vanthienen:
An empirical assessment of kernel type performance for least squares support vector machine classifiers.
KES 2000: 313-316 |
1 | EE | Stijn Viaene,
Bart Baesens,
Tony Van Gestel,
Johan A. K. Suykens,
Dirk Van den Poel,
Jan Vanthienen,
Bart De Moor,
Guido Dedene:
Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.
PKDD 2000: 657-664 |