Purchase Prediction in Database Marketing with the ProbRough System. - Dirk Van den Poel; Zdzislaw Piasta (Rough Sets and Current Trends in Computing, 1998)

Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case. - Stijn Viaene; Bart Baesens; Tony Van Gestel; Johan A. K. Suykens; Dirk Van den Poel; Jan Vanthienen; Bart De Moor; Guido Dedene (PKDD, 2000)

Knowledge discovery in a direct marketing case using least squares support vector machines. - Stijn Viaene; Bart Baesens; Tony Van Gestel; Johan A. K. Suykens; Dirk Van den Poel; Jan Vanthienen; Bart De Moor; Guido Dedene (Int. J. Intell. Syst., 2001)

Wrapped input selection using multilayer perceptrons for repeat-purchase modeling in direct marketing. - Stijn Viaene; Bart Baesens; Dirk Van den Poel; Guido Dedene; Jan Vanthienen (Intell. Syst. Account. Finance Manag., 2001)

Proof Running Two State-Of-The-Art Pattern Recognition Techniques in the Field of Direct Marketing. - Stijn Viaene; Bart Baesens; Guido Dedene; Jan Vanthienen; Dirk Van den Poel (ICEIS, 2002)

Bayesian neural network learning for repeat purchase modelling in direct marketing. - Bart Baesens; Stijn Viaene; Dirk Van den Poel; Jan Vanthienen; Guido Dedene (Eur. J. Oper. Res., 2002)

Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers. - Bart Baesens; Geert Verstraeten; Dirk Van den Poel; Michael Egmont-Petersen; Patrick Van Kenhove; Jan Vanthienen (Eur. J. Oper. Res., 2004)

Customer attrition analysis for financial services using proportional hazard models. - Dirk Van den Poel; Bart Larivière (Eur. J. Oper. Res., 2004)

Customer-adapted coupon targeting using feature selection. - Wouter Buckinx; Elke Moons; Dirk Van den Poel; Geert Wets (Expert Syst. Appl., 2004)

Joint optimization of customer segmentation and marketing policy to maximize long-term profitability. - Jedid-Jah Jonker; Nanda Piersma; Dirk Van den Poel (Expert Syst. Appl., 2004)

Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services. - Bart Larivière; Dirk Van den Poel (Expert Syst. Appl., 2004)

Direct and indirect effects of retail promotions on sales and profits in the do-it-yourself market. - Dirk Van den Poel; Jan De Schamphelaere; Geert Wets (Expert Syst. Appl., 2004)

Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting. - Wouter Buckinx; Dirk Van den Poel (Eur. J. Oper. Res., 2005)

Predicting online-purchasing behaviour. - Dirk Van den Poel; Wouter Buckinx (Eur. J. Oper. Res., 2005)

Predicting customer retention and profitability by using random forests and regression forests techniques. - Bart Larivière; Dirk Van den Poel (Expert Syst. Appl., 2005)

Investigating the post-complaint period by means of survival analysis. - Bart Larivière; Dirk Van den Poel (Expert Syst. Appl., 2005)

Constrained optimization of data-mining problems to improve model performance: A direct-marketing application. - Anita Prinzie; Dirk Van den Poel (Expert Syst. Appl., 2005)

Why promotion strategies based on market basket analysis do not work. - Bernd Vindevogel; Dirk Van den Poel; Geert Wets (Expert Syst. Appl., 2005)

Neural network survival analysis for personal loan data. - Bart Baesens; Tony Van Gestel; M. Stepanova; Dirk Van den Poel; Jan Vanthienen (J. Oper. Res. Soc., 2005)

The impact of sample bias on consumer credit scoring performance and profitability. - Geert Verstraeten; Dirk Van den Poel (J. Oper. Res. Soc., 2005)

Exploiting Randomness for Feature Selection in Multinomial Logit: A CRM Cross-Sell Application. - Anita Prinzie; Dirk Van den Poel (ICDM, 2006)

Using Predicted Outcome Stratified Sampling to Reduce the Variability in Predictive Performance of a One-Shot Train-and-Test Split for Individual Customer Predictions. - Geert Verstraeten; Dirk Van den Poel (ICDM (Posters), 2006)

Incorporating sequential information into traditional classification models by using an element/position-sensitive SAM. - Anita Prinzie; Dirk Van den Poel (Decis. Support Syst., 2006)

Bayesian kernel based classification for financial distress detection. - Tony Van Gestel; Bart Baesens; Johan A. K. Suykens; Dirk Van den Poel; Dirk-Emma Baestaens; Marleen Willekens (Eur. J. Oper. Res., 2006)

Investigating purchasing-sequence patterns for financial services using Markov, MTD and MTDg models. - Anita Prinzie; Dirk Van den Poel (Eur. J. Oper. Res., 2006)

Random Multiclass Classification: Generalizing Random Forests to Random MNL and Random NB. - Anita Prinzie; Dirk Van den Poel (DEXA, 2007)

Predicting home-appliance acquisition sequences: Markov/Markov for Discrimination and survival analysis for modeling sequential information in NPTB models. - Anita Prinzie; Dirk Van den Poel (Decis. Support Syst., 2007)

Banking behaviour after the lifecycle event of "moving in together": An exploratory study of the role of marketing investments. - Bart Larivière; Dirk Van den Poel (Eur. J. Oper. Res., 2007)

Predicting customer loyalty using the internal transactional database. - Wouter Buckinx; Geert Verstraeten; Dirk Van den Poel (Expert Syst. Appl., 2007)

CRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services. - Jonathan Burez; Dirk Van den Poel (Expert Syst. Appl., 2007)

Dynamic Bayesian Networks for Acquisition Pattern Analysis: A Financial-Services Cross-Sell Application. - Anita Prinzie; Dirk Van den Poel (PAKDD Workshops, 2008)

Improving customer complaint management by automatic email classification using linguistic style features as predictors. - Kristof Coussement; Dirk Van den Poel (Decis. Support Syst., 2008)

Separating financial from commercial customer churn: A modeling step towards resolving the conflict between the sales and credit department. - Jonathan Burez; Dirk Van den Poel (Expert Syst. Appl., 2008)

Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. - Kristof Coussement; Dirk Van den Poel (Expert Syst. Appl., 2008)

Random Forests for multiclass classification: Random MultiNomial Logit. - Anita Prinzie; Dirk Van den Poel (Expert Syst. Appl., 2008)

Integrating the voice of customers through call center emails into a decision support system for churn prediction. - Kristof Coussement; Dirk Van den Poel (Inf. Manag., 2008)

Benefits of quantile regression for the analysis of customer lifetime value in a contractual setting: An application in financial services. - Dries F. Benoit; Dirk Van den Poel (Expert Syst. Appl., 2009)

Handling class imbalance in customer churn prediction. - Jonathan Burez; Dirk Van den Poel (Expert Syst. Appl., 2009)

Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers. - Kristof Coussement; Dirk Van den Poel (Expert Syst. Appl., 2009)

Ensembles of Probability Estimation Trees for Customer Churn Prediction. - Koen W. De Bock; Dirk Van den Poel (IEA/AIE (2), 2010)

Extracting Consumers Needs for New Products - A Web Mining Approach. - Dirk Thorleuchter; Dirk Van den Poel; Anita Prinzie (WKDD, 2010)

Ensemble classification based on generalized additive models. - Koen W. De Bock; Kristof Coussement; Dirk Van den Poel (Comput. Stat. Data Anal., 2010)

Improved marketing decision making in a customer churn prediction context using generalized additive models. - Kristof Coussement; Dries F. Benoit; Dirk Van den Poel (Expert Syst. Appl., 2010)

Mining ideas from textual information. - Dirk Thorleuchter; Dirk Van den Poel; Anita Prinzie (Expert Syst. Appl., 2010)

Predicting Website Audience Demographics forWeb Advertising Targeting Using Multi-Website Clickstream Data. - Koen W. De Bock; Dirk Van den Poel (Fundam. Informaticae, 2010)

Improving Purchasing Behavior Predictions by Data Augmentation with Situational Variables. - Philippe Baecke; Dirk Van den Poel (Int. J. Inf. Technol. Decis. Mak., 2010)

RFM Variables Revisited Using Quantile Regression. - Michel Ballings; Dries F. Benoit; Dirk Van den Poel (ICDM Workshops, 2011)

Incorporating Neighborhood Effects in Customer Relationship Management Models. - Philippe Baecke; Dirk Van den Poel (ISMIS, 2011)

An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction. - Koen W. De Bock; Dirk Van den Poel (Expert Syst. Appl., 2011)

Data augmentation by predicting spending pleasure using commercially available external data. - Philippe Baecke; Dirk Van den Poel (J. Intell. Inf. Syst., 2011)

Modeling complex longitudinal consumer behavior with Dynamic Bayesian networks: an Acquisition Pattern Analysis application. - Anita Prinzie; Dirk Van den Poel (J. Intell. Inf. Syst., 2011)

Using NMF for Analyzing War Logs. - Dirk Thorleuchter; Dirk Van den Poel (Future Security, 2012)

Improved Emergency Management by a Loosely Coupled Logistic System. - Dirk Thorleuchter; Joachim Schulze; Dirk Van den Poel (Future Security, 2012)

The Dangers of Using Intention as a Surrogate for Retention in Brand Positioning Decision Support Systems. - Michel Ballings; Dirk Van den Poel (GfKl, 2012)

Temporary Staffing Services: A Data Mining Perspective. - Jeroen D'Haen; Dirk Van den Poel (ICDM Workshops, 2012)

Extracting Information from Sequences of Financial Ratios with Markov for Discrimination: An Application to Bankruptcy Prediction. - Andrey Volkov; Dirk Van den Poel (ICDM Workshops, 2012)

Improving Customer Churn Prediction by Data Augmentation Using Pictorial Stimulus-Choice Data. - Michel Ballings; Dirk Van den Poel; Emmanuel Verhagen (IS-MiS, 2012)

Using Webcrawling of Publicly Available Websites to Assess E-commerce Relationships. - Dirk Thorleuchter; Dirk Van den Poel (SRII Global Conference, 2012)

Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences. - Vera L. Miguéis; Dirk Van den Poel; Ana S. Camanho; João Falcão e Cunha (Adv. Data Anal. Classif., 2012)

Book Review: Ensemble Methods: Foundations and Algorithms. - Dirk Van den Poel (IEEE Intell. Informatics Bull., 2012)

Including spatial interdependence in customer acquisition models: A cross-category comparison. - Philippe Baecke; Dirk Van den Poel (Expert Syst. Appl., 2012)

Customer event history for churn prediction: How long is long enough? - Michel Ballings; Dirk Van den Poel (Expert Syst. Appl., 2012)

Improving customer retention in financial services using kinship network information. - Dries F. Benoit; Dirk Van den Poel (Expert Syst. Appl., 2012)

Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models. - Koen W. De Bock; Dirk Van den Poel (Expert Syst. Appl., 2012)

Modeling partial customer churn: On the value of first product-category purchase sequences. - Vera L. Miguéis; Dirk Van den Poel; Ana S. Camanho; João Falcão e Cunha (Expert Syst. Appl., 2012)

Predicting e-commerce company success by mining the text of its publicly-accessible website. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2012)

Improved multilevel security with latent semantic indexing. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2012)

Analyzing existing customers' websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing. - Dirk Thorleuchter; Dirk Van den Poel; Anita Prinzie (Expert Syst. Appl., 2012)

The role of seed money and threshold size in optimizing fundraising campaigns: Past behavior matters! - Griet Alice Verhaert; Dirk Van den Poel (Expert Syst. Appl., 2012)

Using Eye-Tracking Data of Advertisement Viewing Behavior to Predict Customer Churn. - Michel Ballings; Dirk Van den Poel (ICDM Workshops, 2013)

Analyzing Website Content for Improved R&T Collaboration Planning. - Dirk Thorleuchter; Dirk Van den Poel (WorldCIST, 2013)

Kernel Factory: An ensemble of kernel machines. - Michel Ballings; Dirk Van den Poel (Expert Syst. Appl., 2013)

Predicting customer profitability during acquisition: Finding the optimal combination of data source and data mining technique. - Jeroen D'Haen; Dirk Van den Poel; Dirk Thorleuchter (Expert Syst. Appl., 2013)

Technology classification with latent semantic indexing. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2013)

Protecting research and technology from espionage. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2013)

Web mining based extraction of problem solution ideas. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2013)

Weak signal identification with semantic web mining. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2013)

Improving customer acquisition models by incorporating spatial autocorrelation at different levels of granularity. - Philippe Baecke; Dirk Van den Poel (J. Intell. Inf. Syst., 2013)

Enhanced decision support in credit scoring using Bayesian binary quantile regression. - Vera L. Miguéis; Dries F. Benoit; Dirk Van den Poel (J. Oper. Res. Soc., 2013)

Using Text Summarizing to Support Planning of Research and Development. - Dirk Thorleuchter; Dirk Van den Poel (WorldCIST (1), 2014)

Cash demand forecasting in ATMs by clustering and neural networks. - Kamini Venkatesh; Vadlamani Ravi; Anita Prinzie; Dirk Van den Poel (Eur. J. Oper. Res., 2014)

Quantitative cross impact analysis with latent semantic indexing. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2014)

Semantic compared cross impact analysis. - Dirk Thorleuchter; Dirk Van den Poel (Expert Syst. Appl., 2014)

Semantic weak signal tracing. - Dirk Thorleuchter; Tobias Scheja; Dirk Van den Poel (Expert Syst. Appl., 2014)

CRM in social media: Predicting increases in Facebook usage frequency. - Michel Ballings; Dirk Van den Poel (Eur. J. Oper. Res., 2015)

Evaluating multiple classifiers for stock price direction prediction. - Michel Ballings; Dirk Van den Poel; Nathalie Hespeels; Ruben Gryp (Expert Syst. Appl., 2015)

Equity price direction prediction for day trading: Ensemble classification using technical analysis indicators with interaction effects. - Dirk Van den Poel; Celine Chesterman; Maxim Koppen; Michel Ballings (CEC, 2016)

The added value of Facebook friends data in event attendance prediction. - Matthias Bogaert; Michel Ballings; Dirk Van den Poel (Decis. Support Syst., 2016)

Integrating expert knowledge and multilingual web crawling data in a lead qualification system. - Jeroen D'Haen; Dirk Van den Poel; Dirk Thorleuchter; Dries F. Benoit (Decis. Support Syst., 2016)

The added value of auxiliary data in sentiment analysis of Facebook posts. - Matthijs Meire; Michel Ballings; Dirk Van den Poel (Decis. Support Syst., 2016)

Identification of interdisciplinary ideas. - Dirk Thorleuchter; Dirk Van den Poel (Inf. Process. Manag., 2016)

Identifying Soccer Players on Facebook Through Predictive Analytics. - Matthias Bogaert; Michel Ballings; Martijn Hosten; Dirk Van den Poel (Decis. Anal., 2017)

The added value of social media data in B2B customer acquisition systems: A real-life experiment. - Matthijs Meire; Michel Ballings; Dirk Van den Poel (Decis. Support Syst., 2017)

Incorporating sequential information in bankruptcy prediction with predictors based on Markov for discrimination. - Andrey Volkov; Dries F. Benoit; Dirk Van den Poel (Decis. Support Syst., 2017)

Latency Measurement of Fine-Grained Operations in Benchmarking Distributed Stream Processing Frameworks. - Giselle van Dongen; Bram Steurtewagen; Dirk Van den Poel (BigData Congress, 2018)

Evaluating the importance of different communication types in romantic tie prediction on social media. - Matthias Bogaert; Michel Ballings; Dirk Van den Poel (Ann. Oper. Res., 2018)

Evaluating multi-label classifiers and recommender systems in the financial service sector. - Matthias Bogaert; Justine Lootens; Dirk Van den Poel; Michel Ballings (Eur. J. Oper. Res., 2019)

Machine learning refinery sensor data to predict catalyst saturation levels. - Bram Steurtewagen; Dirk Van den Poel (Comput. Chem. Eng., 2020)

Leveraging latent representations for milk yield prediction and interpolation using deep learning. - Arno Liseune; Matthieu Salamone; Dirk Van den Poel; Bonifacius Van Ranst; Miel Hostens (Comput. Electron. Agric., 2020)

Evaluation of Stream Processing Frameworks. - Giselle van Dongen; Dirk Van den Poel (IEEE Trans. Parallel Distributed Syst., 2020)

A Performance Analysis of Fault Recovery in Stream Processing Frameworks. - Giselle van Dongen; Dirk Van den Poel (IEEE Access, 2021)

Influencing Factors in the Scalability of Distributed Stream Processing Jobs. - Giselle van Dongen; Dirk Van den Poel (IEEE Access, 2021)

Adding interpretability to predictive maintenance by machine learning on sensor data. - Bram Steurtewagen; Dirk Van den Poel (Comput. Chem. Eng., 2021)

Leveraging sequential information from multivariate behavioral sensor data to predict the moment of calving in dairy cattle using deep learning. - Arno Liseune; Dirk Van den Poel; Peter R. Hut; Frank J. C. M. van Eerdenburg; Miel Hostens (Comput. Electron. Agric., 2021)

Predicting the milk yield curve of dairy cows in the subsequent lactation period using deep learning. - Arno Liseune; Matthieu Salamone; Dirk Van den Poel; Bonifacius Van Ranst; Miel Hostens (Comput. Electron. Agric., 2021)

Predicting Self-declared Movie Watching Behavior Using Facebook Data and Information-Fusion Sensitivity Analysis. - Matthias Bogaert; Michel Ballings; Rob Bergmans; Dirk Van den Poel (Decis. Sci., 2021)

Box office sales and social media: A cross-platform comparison of predictive ability and mechanisms. - Matthias Bogaert; Michel Ballings; Dirk Van den Poel; Asil Oztekin (Decis. Support Syst., 2021)

Predicting donation behavior: Acquisition modeling in the nonprofit sector using Facebook data. - Lisa Schetgen; Matthias Bogaert; Dirk Van den Poel (Decis. Support Syst., 2021)

Do Mobile Phone Data Provide a Better Denominator in Crime Rates and Improve Spatiotemporal Predictions of Crime? - Anneleen Rummens; Thom Snaphaan; Nico Van de Weghe; Dirk Van den Poel; Lieven J. R. Pauwels; Wim Hardyns (ISPRS Int. J. Geo Inf., 2021)

360 Degrees rumor detection: When explanations got some explaining to do. - Bram Janssens; Lisa Schetgen; Matthias Bogaert; Matthijs Meire; Dirk Van den Poel (Eur. J. Oper. Res., 2024)

B2Boost: instance-dependent profit-driven modelling of B2B churn. - Bram Janssens; Matthias Bogaert; Astrid Bagué; Dirk Van den Poel (Ann. Oper. Res., 2024)