François Fouss
SSH/LSM Louvain School of Management (LSM)
SSH/LRIM Louvain Research Institute in Management and Organizations (LouRIM)
SST/ICTM Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM)
Postal address
LSM - Bâtiment BM1.01.01
Chaussée de Binche 151
7000 Mons
François Fouss is Professor in Information Systems at Louvain School of Management (LSM), Université catholique de Louvain (UCLouvain), in Belgium. He is attached to the Louvain Research Institute in Management and Organizations (LouRIM).
His courses focus on information technology and the digital society, from basic concepts to network/graph analysis, through algorithms and programming, data management and data science/analytics - see here for a summary infography (in French).
His research focuses on NTIC and on data analysis, and is developped in various areas such as graph theory, recommender systems, data mining, machine learning, or clustering. His work is twofold, on the one hand in the development of new algorithms, and on the other hand in the analysis of the impact of NTIC.
Degrees
| Year | Label | School |
|---|---|---|
| 1998 | Candidat ingénieur de gestion | Université catholique de Louvain (Belgique) |
| 2001 | Ingénieur de gestion | Université catholique de Louvain (Belgique) |
| 2002 | Diplômé d'études spécialisées en informatique de gestion - Master in Information Systems | Université catholique de Louvain (Belgique) |
| 2007 | Docteur en sciences de gestion | Université catholique de Louvain (Belgique) |
Learning units for 2024
| Label | Code |
|---|---|
| Programming and Algorithms | MINFO1201 |
| Data Management | MINFO1301 |
| Data Analytics | MLSMM2116 |
| Web Mining | MLSMM2153 |
| Information Technology and Digital Society | MQANT1109 |
Satinet, Chloé ; Fouss, François ; Saerens, Marco ; Leleux, Pierre. In-processing and post-processing strategies for balancing accuracy and sustainability in product recommendations. In: Electronic Commerce Research and Applications, (2024). doi:10.1016/j.elerap.2024.101433.
Satinet, Chloé ; Ducarroz, Caroline ; Fouss, François. Understanding the impact of sustainability-oriented recommender systems on consumers’ choices (Louvain Research Institute in Management and Organizations Working Paper Series; ), 2024.
Satinet, Chloé ; Fouss, François ; Saerens, Marco ; Leleux, Pierre. In-Processing and Post-Processing Strategies for Balancing Accuracy and Sustainability in Product Recommendations. 1st Interdisciplinary Conference on Management, Information Technology and Computer Sciences (Lille, France, du 25/05/2023 au 26/05/2023).
Satinet, Chloé ; Fouss, François ; Saerens, Marco ; Leleux, Pierre. In-Processing and Post-Processing Strategies for Balancing Accuracy and Sustainability in Product Recommendations (Louvain Research Institute in Management and Organizations Working Paper Series; ), 2023.
Satinet, Chloé ; Fouss, François. A Supervised Machine Learning Classification Framework for Clothing Products’ Sustainability. In: Sustainability, Vol. 14, no. 3 (2022). doi:10.3390/su14031334.
Raneri Santo ; Lecron Fabian ; Hermans, Julie ; Fouss, François. Predictions through Lean Startup? Harnessing AI-based predictions under uncertainty. In: International Journal of Entrepreneurial Behavior & Research, (2022) (Accepté/Sous presse).
Satinet, Chloé ; Fouss, François. A Supervised Machine Learning Classification Framework for Assessing the Sustainability of Clothing Products (Louvain Research Institute in Management and Organizations Working Paper Series), 2022.
Fouss, François ; Fernandes, Elora. A closer-to-reality model for comparing relevant dimensions of recommender systems, with application to novelty. In: Information, Vol. 12, no.12, p. 500 (2021). doi:10.3390/info12120500.
Vandenbulcke Virginie ; Ducarroz, Caroline ; Fouss, François. Collaborative recommendations in the mass retail sector - The role of reactance (Soumis).
Satinet, Chloé ; Fouss, François. A Supervised Machine Learning Classification Framework for Clothing Products’ Sustainability. Conférence sur la recherche interdisciplinaire et transdisciplinaire « Transition et Développement durable ». (Louvain-la-Neuve, 26/11/2021).
Vancompernolle Vromman, Flore ; Fouss, François. Filter-bubble created by collaborative filtering algorithms themselves, fact or fiction? An experimental comparison. Proceedings of the Data Analytics on Social Media Workshop of the 2021 IEEE/WIC/ACM International Conference on Web Intelligence. In: Proceedings of the Data Analytics on Social Media Workshop of the 2021 IEEE/WIC/ACM International Conference on Web Intelligence, (2021). doi:10.1145/3498851.3498945.
Satinet, Chloé ; Fouss, François. An aggregated model assessing the risk of job automation – Application to Belgian employment data (Louvain Research Institute in Management and Organizations Working Paper Series; 2021/03), 2021. 12 p.
Fernandes, Elora ; Lecron, Fabian ; Fouss, François. Adapted Collaborative Filtering Algorithms through Diversity and Novelty, 2019. 20 p.
Lecron, Fabian ; Fouss, François. An Optimization Model for Collaborative Recommendation Using a Covariance-Based Regularizer. In: Data Mining and Knowledge Discovery, Vol. 32, no.3, p. 651-674 (2018). doi:10.1007/s10618-018-0552-3.
Sommer, Félix ; Fouss, François ; Saerens, Marco. Modularity-driven kernel k-means for community detection. In: Lecture Notes in Computer Science - ICANN 2017 International Conference on Artificial Neural Networks, Vol. 10614, p. 423-433 (2017). doi:10.1007/978-3-319-68612-7_48.
Vandenbulcke, Virginie ; Ducarroz, Caroline ; Fouss, François. Personalized Collaborative Recommendations in the Mass-retailing Sector: the Impact of the Recommended Products and the Accompanying Message on Consumer Behavior. EMAC (European Marketing Academy) - 46th Annual Conference (Groningen (Netherlands), du 23/05/2017 au 26/05/2017).
Vandenbulcke, Virginie ; Ducarroz, Caroline ; Fouss, François. Recommandations collaboratives personnalisées : Quel impact sur le comportement du consommateur en grande distribution ?. 33ème Congrès International de l'AFM (Association Française du Marketing) (Tours, France, du 17/05/2017 au 19/05/2017).
Sommer, Félix ; Lecron, Fabian ; Fouss, François. Recommender systems: the case of repeated interaction in matrix factorization. International Conference on Web Intelligence (Leipzig, Germany , du 23/08/2017 au 26/05/2018). In: WI'17 Proceedings of the International Conference on Web Intelligence, ACM : New York, 2017. 978-1-4503-4951-2, p. 843-847 . doi:10.1145/3106426.3106522 .
Sommer, Felix ; Fouss, François ; Saerens, Marco. Modularity-driven kernel k-means for community detection (Louvain Research Institute in Management and Organizations Working Paper Series; 2017/21), 2017. 15 p.
vandenbulcke virginie ; Ducarroz, Caroline ; Fouss, François. Personalized Collaborative recommenations in the Mass-retailing Sector: the Impact of the Recommended Products and the Accompanying Message on Consume Behavior (Working Paper LSM; 2017/16), 2017.
Sommer, Félix ; Fouss, François ; Saerens, Marco. Comparison of Graph Node Distances on Clustering Tasks. In: Lecture Notes in Computer Science - ICANN 2016 International Conference on Artificial Neural Networks, Vol. 9886, p. 192-201 (2016). doi:10.1007/978-3-319-44778-0_23.
Fouss, François. Le Big Data est à nous!. In: La Libre, Vol. /, no./, p. / (2015).
Vandenbulcke, Virginie ; Ducarroz, Caroline ; Fouss, François. Evaluating the impact of personalized recommendations: Application in the mass-retailing sector. . 44th European Marketing Academy (EMAC) Conference (Leuven (Belgium), du 26/05/2015 au 29/05/2015).
Sommer, Felix ; Fouss, François ; Saerens, Marco. Clustering using a Sum-Over-Forests weighted kernel k-means approach (Louvain School of Management Working Paper Series; 2015/22), 2015. 34 p.
Senelle, Mathieu ; Garcia Diez, Silvia ; Mantrach, Amin ; Shimbo, Masashi ; Saerens, Marco ; Fouss, François. The Sum-over-Forests density index: identifying dense regions in a graph. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 36, no. 6, p. 1268-1274 (2014). doi:10.1109/TPAMI.2013.227.
Van Parijs, Clémentine ; Fouss, François. Improving accuracy by reducing the importance of hubs in nearest-neighbor recommendations. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (Bruges).
Senelle, Mathieu ; Saerens, Marco ; Fouss, François. The Sum-over-Forests clustering. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (Bruges). In: Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2014.
vandenbulcke virginie ; Ducarroz, Caroline ; Fouss, François. Evaluationg the impact of personalized recommendations : Application in the mass-retailing sector (Working Paper LSM; 2014/22), 2014.
Sommer, Felix ; Fouss, François. Learning with product graphs and multiple labels (Working Paper LSM; 2014/20), 2014.
Vandenbulcke, Virginie ; Lecron, Fabian ; Ducarroz, Caroline ; Fouss, François. Customer segmentation based on a collaborative recommendation system: application to a retail company. Conference of European Marketing Academy (EMAC) (Istanbul). In: Proceedings of the 2013 conference of European Marketing Academy, 2013.
Françoisse, Kevin ; Fouss, François ; Saerens, Marco. A Link-Analysis-Based Discriminant Analysis for Exploring Partially Labeled Graphs. In: Pattern Recognition Letters, Vol. 34, no. 2, p. 146–154 (2013). doi:10.1016/j.patrec.2012.07.025.
Fouss, François ; Françoisse, Kevin ; Yen, Luh ; Pirotte, Alain ; Saerens, Marco. An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. In: Neural Networks, Vol. 31, p. 53-72 (2012). doi:10.1016/j.neunet.2012.03.001.
Yen, Luh ; Saerens, Marco ; Fouss, François. A Link Analysis Extension of Correspondence Analysis for Mining Relational Databases. In: IEEE Transactions on Knowledge and Data Engineering, Vol. 23, no.4, p. 481-495 (2011). doi:10.1109/TKDE.2010.142.
Garcia Diez, Silvia ; Fouss, François ; Shimbo, Masashi ; Saerens, Marco. A sum-over-paths extension of edit distances accounting for all sequence alignments. In: Pattern Recognition, Vol. 44, no.6, p. 1172-1182 (2011). doi:10.1016/j.patcog.2010.11.020.
Garcia Diez, Silvia ; Saerens, Marco ; Senelle, Mathieu ; Fouss, François. A Simple-cycles weighted kernel based on harmony structure for similarity retrieval. Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011) (Miami, Florida, USA, du 24/10/2011 au 28/10/2011).
Fouss, François ; Achbany, Youssef ; Saerens, Marco. A probabilistic reputation model based on transaction ratings. In: Information Sciences, Vol. 180, no. 11, p. 2095-2123 (Juin 2010). doi:10.1016/j.ins.2010.01.020.
Fouss, François. Collaborative-recommendation systems and link analysis. In: Pascal Francq, Collaborative Search and Communities of Interest: Trends in Knowledge Sharing and Assessment, 2010. 978-1-6152-0841-8.
Fouss, François. Introduction to recommender systems. In: Pascal Francq, Collaborative search and communities of interest [electronic resource] : trends in knowledge sharing and assessment, 2010. 9781615208425. doi:10.4018/978-1-61520-841-8.
Garcia Diez, Silvia ; Fouss, François ; Shimbo, Masashi ; Saerens, Marco. Normalized Sum-over-Paths Edit Distances. International Conference on Pattern Recognition (Istanbul, Turkey, du 23/08/2010au 26/08/2010).
Yen, Luh ; Fouss, François ; Decaestecker, Christine ; Francq, Pascal ; Saerens, Marco. Graph nodes clustering with the sigmoid commute-time kernel: A comparative study. In: Data and Knowledge Engineering, Vol. 68, no. 3, p. 338-361 (Mars 2009). doi:10.1016/j.datak.2008.10.006.
Saerens, Marco ; Fouss, François ; Achbany, Youssef ; Yen, Luh. Randomized shortest-path problems: Two related models. In: Neural computation, Vol. 21, no. 8, p. 2363-2404 (Août 2009). doi:10.1162/neco.2009.11-07-643.
Achbany, Youssef ; Jureta, Ivan ; Faulkner, Stéphane ; Fouss, François. Continually Learning Optimal Web Service Compositions. In: IEEE Transactions on Services Computing, Vol. 1, Iss. 3, p. 141-154 (2008). doi:10.1109/TSC.2008.12.
Achbany, Youssef ; Fouss, François ; Yen, Luh ; Pirotte, Alain ; Saerens, Marco. Tuning continual exploration in reinforcement learning: An optimality property of the Boltzmann strategy. In: Neurocomputing, Vol. 71, no. 13-15, p. 2507-2520 (2008). doi:10.1016/j.neucom.2007.11.040.
Herssens, Caroline ; Faulkner, Stéphane ; Fouss, François ; Jureta, Ivan. A Framework for QoS Driven Selection of Services. IEEE International Conference on Services Computing (Honolulu, Hawaii, USA, du 08/07/2008au 11/07/2008).
Fouss, François ; Saerens, Marco. Evaluating performance of recommender systems: An experimental comparison. IEEE/WIC/ACM International Conference on Web Intelligence (Sydney, Australia, du 09/12/2008 au 12/12/2008).
Fouss, François ; Achbany, Youssef ; Saerens, Marco. A probabilistic reputation model (IAG - LSM Working Papers; 08/20), 2008.
Yen, Luh ; Saerens, Marco ; Francq, Pascal ; Decaestecker, Christine ; Fouss, François. Graph Nodes Clustering based on the Commute-Time Kernel. In: Lecture Notes in Computer Science, Vol. 4426, p. 1037-1045 (2007). doi:10.1007/978-3-540-71701-0_117.
Fouss, François ; Pirotte, Alain ; Renders, Jean-Michel ; Saerens, Marco. Random-walk computation of similarities between nodes of a graph, with application to collaborative recommendation. In: IEEE Transactions on Knowledge and Data Engineering, Vol. 19, no. 3, p. 355-369 (Mars 2007). doi:10.1109/TKDE.2007.46.
Fouss, François. Measures of similarity on graphs : Investigation and application to collaborative recommendation.
Achbany, Youssef ; Saerens, Marco ; Pirotte, Alain ; Yen, Luh ; Fouss, François. Optimal Tuning of Continual Online Exploration in Reinforcement Learning. In: Lecture Notes in Computer Science, Vol. 4131 (2006).
Fouss, François ; Yen, Luh ; Pirotte, Alain ; Saerens, Marco. An experimental investigation of graph kernels on a collaborative recommendation task. IEEE International Conference on Data Mining (ICDM 2006) (Hong Kong, China, du 18/12/2006 au 22/12/2006).
Achbany, Youssef ; Fouss, François ; Yen, Luh ; Pirotte, Alain ; Saerens, Marco. Optimal tuning of continual, online, exploration in reinforcement learning. 16th International Conference on Artificial Neural Networks (Berlin, 2006). In: Lecture Notes in Computer Science, Springer: Berlin, 2006. 978-3-540-38625-4, Vol. 4131, p. 790-800 (2006).
Fouss, François ; Pirotte, Alain ; Saerens, Marco ; Renders, Jean-Michel ; Yen, Luh. A novel way of computing similarities between nodes of a graph, with application to collaborative filtering and subspace projection of the graph nodes (IAG - LSM Working Papers; 06/08), 2006. 43 p.
Fouss, François ; Renders, Jean-Michel ; Pirotte, Alain ; Saerens, Marco. A novel way of computing similarities between nodes of a graph, with application to collaborative recommendation. IEEE WIC/ACM International Joint Conference on Web Intelligence (Compiègne, France, du 19/09/2005 au 22/09/2005).
Yen, Luh ; VanVyve, Denise J. ; Wouters, Fabien ; Fouss, François ; Verleysen, Michel ; Saerens, Marco. Clustering using a random walk-based distance measure. 13th European Symposium on Artificial Neural Networks (du 27/04/2005 au 2005/04/29). In: Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005. 2-930307-05-6, p. 317-324.
Saerens, Marco ; Fouss, François. HITS is principal components analysis. 2005 IEEE/ACM International Joint Conference on Web Intelligence (du 2005/09/19 au 2005/09/22), p. 782-785 (2005).
Fouss, François ; Saerens, Marco ; Pirotte, Alain ; Kolp, Manuel ; Faulkner, Stéphane. Web recommendation system based on a Markov-chain model. International Conference on Enterprise Information Systems (ICEIS 2005) (Miami, USA, du 24/05/2005 au 28/05/2005).
Saerens, Marco ; Fouss, François. Hits is PCA (IAG Working Papers; 2005/125 ), 2005.
Saerens, Marco ; Fouss, François ; Yen, Luh ; Dupont, Pierre. The principal components analysis of a graph and its relationships to spectral clustering (IAG Working Papers; 2005/124 ), 2005.
Fouss, François ; Faulkner, Stéphane ; Kolp, Manuel ; Pirotte, Alain ; Saerens, Marco. Web recommendation system based on a markov-chain model (IAG Working Papers; 2005/123 ), 2005.
Fouss, François ; Saerens, Marco. Yet another method for combining classifiers outputs: A maximum entropy approach. In: Lecture Notes in Computer Science, Vol. 3077 (2004).
Fouss, François ; Pirotte, Alain ; Saerens, Marco. A Novel Way of Computing Dissimilarities between Nodes of a Graph, with Application to Collaborative Filtering. Proceedings of the Workshop on Statistical Approaches for Web Mining, p. 26-37 (2004).
Saerens, Marco ; Fouss, François ; Dupont, Pierre ; Pirotte, Alain. Collaborative filtering based on random walks on a graph. Workshop on Large Networks (UCL, LLN, December 1, 2004).
Fouss, François ; Renders, Jean-Michel ; Saerens, Marco. Some relationships between Kleinberg's hubs and authorities, correspondence analysis, and the Salsa algorithm. International Conference on the Statistical Analysis of Textual Data (JADT 2004) (Louvain-la-Neuve, Belgium).
Fouss, François ; Renders, Jean-Marc ; Saerens, Marco. Some relationships between between Kleinberg’s hubs and authorities, correspondence analysis and Markov chains. 7th International Conference on the Statistical Analysis of Textual Data, p. 445-455 (2004).
Fouss, François ; Pirotte, Alain ; Saerens, Marco. The Application of New Concepts of Dissimilarities between Nodes of a Graph to Collaborative Filtering. Workshop on Statistical Approaches for Web Mining (SAWM) (Pisa, Italy).
Saerens, Marco ; Fouss, François ; Yen, Luh ; Dupont, Pierre. The principal components analysis of a graph, and its relationships to spectral clustering. Machine Learning: ECML 2004, 15th European Conference on Machine Learning. In: Lecture Notes in Computer Science, Vol. 3201, p. 371-383 (2004).
Saerens, Marco ; Fouss, François ; Yen, Luh ; Dupont, Pierre. The principle components analysis of a graph, and its relationships to spectral clustering. Machine Learning: ECML 2004. 15th European Conference on Machine Learning. Proceedings (Pisa, Italy, 20-24 September 2004). In: Machine Learning: ECML 2004. 15th European Conference on MachineLearning. Proceedings (Lecture Notes in Artificial IntelligenceVol.3201), Springer-verlag, 2004. 3-540-23105-6, p. 371-383.
Saerens, Marco ; Fouss, François. Yet another method for combining experts opinions. 5th International Workshop on Multiple Classifier Systems, Vol. 3077, p. 82-91 (2004).
Fouss, François ; Saerens, Marco. A maximum entropy approach to multiple classifiers combination (IAG - LSM Working Papers; 04/107), 2004. 15 p.
Fouss, François ; Renders, Jean-Michel ; Saerens, Marco. Links between Kleinberg's hubs and authorities, correspondence analysis and Markov chains. IEEE International Conference on Data Mining (ICDM 2003) (Melbourne, USA).
Donnay, Aymerick ; Fouss, François ; Kolp, Manuel ; Massart, David ; Pirotte, Alain. Analyse oriente objet de processus sidérurgiques de type cokier (IAG - LSM Working Papers; 03/86), 2003. 24 p.
Donnay, Aymerick ; Fouss, François ; Kolp, Manuel ; Massart, David ; Pirotte, Alain. Analyse orientée objet de processus sidérurgiques de type cokier (IAG Working Papers; 2003/86 ), 2003.
Fouss, François ; Renders, Jean-Michel ; Saerens, Marco. Links between Kleinberg's hubs and authorities, correspondence analysis, and Markov chains (ECON Discussion Papers IAG Working Papers; 2003/101 2003/102 ), 2003.
Fouss, François ; Ibarz, Marti ; Kolp, Manuel ; Pirotte, Alain. Steel production data warehouse reengineering (ECON Discussion Papers IAG Working Papers; 2003/89 2003/85 ), 2003.