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Prof.Dr.Ir. U. Kaymak

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Uzay Kaymak

Prof.Dr.Ir. U. Kaymak

Professor of Intelligence and Computation in Economics

Department of Econometrics

Erasmus School of Economics

Erasmus University Rotterdam

 

Personal website: http://people.few.eur.nl/kaymak/


 

Profile

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Professional experience

Present position
Irregular Staff
University Erasmus University Rotterdam
School Erasmus School of Economics
Department Econometrics
   
Other position

Research

Uzay Kaymak is endowed professor of Intelligence and Computation in Economics at Erasmus School of Economics. His research is at the interface of computer science and economics. He studies the use of ICT for intelligent decision support systems and the application of artificial intelligence within business processes. His research is characterized by innovative solutions to problems originating from business practice. He has published more than 150 scientific papers on fuzzy systems, computational intelligence and business.

Management Science
Funder
Role Member
 

Publications

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Scholarly publications (193)
  • Milea, D.V., Frasincar, F. & Kaymak, U. (2012). Temporal Optimizations and Temporal Cardinality in the tOWL Language. International Journal of Web Engineering and Technology, 7(1), 45-64.
  • Hogenboom, F.P., Winter, M.R., Jansen, M., Hogenboom, A.C., Frasincar, F. & Kaymak, U. (2012). Event-Based Historical Value-at-Risk. In IEEE Computational Intelligence for Financial Engineering & Economics 2012 (CIFEr 2012).
  • Milea, D.V., Frasincar, F. & Kaymak, U. (2012). tOWL: A Temporal Web Ontology Language. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 42(1), 268-281.
  • Milea, D.V., Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Frasincar, F. (2011). A Fuzzy Model of a European Index Based on Automatically Extracted Content Information. In 2011 IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFeEr 2011). IEEE Computational Intelligence Society.
  • Hogenboom, A.C., Iterson, P. v., Heerschop, B.M.W.T., Frasincar, F. & Kaymak, U. (2011). Analyzing Sentiment while Accounting for Negation Scope and Strength. In P. de Causmaecker, J. Maervoet, T. Messelis, K. Verbeeck & T. Vermeulen (Eds.), Twenty-Third Benelux Conference on Artificial Intelligence (BNAIC 2011) (pp. 395-396). Nevelland.
  • Hogenboom, F.P., Frasincar, F., Kaymak, U. & Jong, F.M.G. de (2011). News Recommendations using CF-IDF. In P. de Causmaecker, J. Maervoet, T. Messelis, K. Verbeeck & T. Vermeulen (Eds.), Proceedings of the Twenty-Third Benelux Conference on Artificial Intelligence (BNAIC 2011) (pp. 397-398). Gent, Belgium: Nevelland.
  • Hogenboom, F.P., Frasincar, F., Kaymak, U. & Jong, F.M.G. de (2011). An Overview of Event Extraction from Text. In M. van Erp, W.R. van Hage, L. Hollink, A. Jameson & R. Troncy (Eds.), Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web (DeRiVE 2011) at Tenth International Semantic Web Conference (ISWC 2011) (pp. 48-57). CEUR-WS.org.
  • Heerschop, B.M.W.T., Goossen, F., Hogenboom, A.C., Frasincar, F., Kaymak, U. & Jong, F.M.G. de (2011). Polarity Analysis of Texts using Discourse Structure. In Twentieth ACM Conference on Information and Knowledge Management (CIKM 2011) (pp. 1061-1070). ACM.
  • Hogenboom, A.C., Iterson, P. v., Heerschop, B.M.W.T., Frasincar, F. & Kaymak, U. (2011). Determining Negation Scope and Strength in Sentiment Analysis. In IEEE International Conference on Systems, Man, and Cybernetics 2011 (SMC 2011) (pp. 2589-2594). IEEE.
  • Hogenboom, A.C., Hogenboom, F.P., Frasincar, F., Kaymak, U., Meer, O. v.d. & Schouten, K. (2011). Detecting Economic Events Using a Semantics-Based Pipeline. In A. Hameurlain, S. Liddle, K. Schewe & X. Zhou (Eds.), Database and Expert Systems Applications Vol. 6860. Lecture Notes in Computer Science (pp. 440-447). Berlin: Springer.
  • Soppe, A.B.M., Schauten, M.B.J., Soppe, J. & Kaymak, U. (2011). Corporate Social Responsibility Reputation (CSRR): Do Companies Comply with their Raised CSR Expectations (forthcoming). Corporate Reputation Review, 14(4), 300-323.
  • Goossen, F., IJntema, W., Frasincar, F., Hogenboom, F.P. & Kaymak, U. (2011). News Personalization using the CF-IDF Semantic Recommender. In R. Akerkar (Ed.), International Conference on Web Intelligence, Mining and Semantics (WIMS 2011). ACM.
  • Hinojosa, W.M., Nefti, S. & Kaymak, U. (2011). System Control With Generalized Probabilistic Fuzzy-Reinforcement Learning. IEEE Transactions on Fuzzy Systems, 19(1), 51-64.
  • Waltman, L.R., Eck, N.J.P. van, Dekker, R. & Kaymak, U. (2011). An Evolutionary Model of Price Competition Among Spatially Distributed Firms. (EI report serieEI 2011-09 ). Rotterdam: Econometric Institute.
  • Heerschop, B.M.W.T., van Iterson, P., Hogenboom, A.C., Frasincar, F. & Kaymak, U. (2011). Analyzing Sentiment in a Large Set of Web Data While Accounting for Negation. In E. Mugellini, P.S. Szczepaniak, M.C Pettenati & M. Sokhn (Eds.), Advances in Intelligent Web Mastering - 3 (Advances in Intelligent and Soft Computing, 86) (pp. 195-205). Berlin: Springer.
  • Waltman, L., Van Eck, N.J., Dekker, R. & Kaymak, U. (2011). Economic modeling using evolutionary algorithms: the effect of binary encoding of strategies. Journal of Evolutionary Economics, 21(5), 737-756.
  • Heerschop, B.M.W.T., van Iterson, P., Hogenboom, A.C., Frasincar, F. & Kaymak, U. (2011). Accounting for Negation in Sentiment Analysis. In Eleventh Dutch-Belgian Information Retrieval Workshop (DIR 2011) (pp. 38-39).
  • Bosma, R., Kaymak, U., Van Den Berg, J., Udo, H.M.J. & Verreth, J.A.J. (2011). Using fuzzy logic modelling to simulate farmers' decision making on diversification and integration in the Mekong Delta, Vietnam. Soft Computing, 15(2), 295-310.
  • Meer, J. van der, Boon, F., Hogenboom, F.P., Frasincar, F. & Kaymak, U. (2011). A Framework for Automatic Annotation of Web Pages Using the Google Rich Snippets Vocabulary. In W. Chu, W.E. Wong, M.J. Palakal & C.-C. Hung (Eds.), Twenty-Sixth Symposium on Applied Computing (SAC 2011) (pp. 765-772). ACM.
  • Pereira, R.D.M.A., Almeida e Santos Nogueira, R.J. de, Kaymak, U., Vieira, S.M., Sousa, J.M.C., Reti, S.R., Howell, M.D. & Finkelstein, S.N. (2011). Predicting septic shock outcomes in a database with missing data using fuzzy modeling: Influence of pre-processing techniques on real-world data-based classification. In Proceedings of the 2011 IEEE International Conference on Fuzzy Systems (pp. 2507-2512).
  • Hogenboom, F.P., Frasincar, F., Vandic, D., Meer, J. van der, Boon, F. & Kaymak, U. (2011). Automatically Annotating Web Pages Using Google Rich Snippets. In C. Boscarino, K. Hofmann, V. Jijkoun, E. Meij & W. Weerkamp (Eds.), Eleventh Dutch-Belgian Information Retrieval Workshop (DIR 2011) (pp. 42-43).
  • Berg, J. van den, Kaymak, U. & Almeida e Santos Nogueira, R.J. de (2011). Function Approximation Using Probabilistic Fuzzy Systems. (ERIM Report Series Research in Management-ERS-2011-026-LIS ). Rotterdam: Erasmus Research Institute of Management (ERIM).
  • Almeida e Santos Nogueira, R.J. de, Basturk, N., Kaymak, U. & Sousa, J.M.C. (2011). Fuzzy GARCH models. In Book of Abstracts of the Fifth International conference on Computational and Financial Econometrics and Fourth Workshop of the ERCIM Working Group on Computing and Statistics (pp. 114).
  • Vieira, S.M., Kaymak, U. & Sousa, J.M.C. (2010). Cohen's kappa coefficient as a performance measure for feature selection. In Proceedings of the 2010 IEEE International Conference Fuzzy Systems (pp. 1-8). Barcelona, Spain: IEEE.
  • Vieira, S.M., Sousa, J.M.C. & Kaymak, U. (2010). Ant Feature Selection Using Fuzzy Decision Functions. In W.A. Lodwick & J. Kacprzyk (Eds.), Fuzzy Optimization: Recent Developments and Applications (Studies in Fuzziness and Soft Computing, 254) (pp. 343-364). Berlin: Springer.
  • Lovric, M., Kaymak, U. & Spronk, J. (2010). A conceptual model of investor behavior. In S. Nefti & J.O. Gray (Eds.), Advances in Cognitive Systems (IET Control Engineering Series, 71) (pp. 369-394). London, UK: Institution of Engineering and Technology.
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2010). TS-Models from Evidential Clustering. In R. Kruse, F. Hoffmann & E. Hüllermeier (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods. - Part I (Communications in Computer and Information Science, 80) (pp. 228-237). Berlin: Springer.
  • Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Sousa, J.M.C. (2010). A New Approach to Dealing With Missing Values in Data-driven Fuzzy Modeling. In Proceedings of the 2010 IEEE International Conference on Fuzzy Systems (pp. 1-7). Barcelona, Spain: IEEE.
  • Milea, D.V., Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Frasincar, F. (2010). A Fuzzy Model of the MSCI EURO Index Based on Content Analysis of European Central Bank Statements. In 2010 IEEE International Conference Fuzzy Systems (Fuzz-IEEE 2010) (pp. 1-7). Barcelona: IEEE.
  • Milea, D.V., Sharef, N.M., Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Frasincar, F. (2010). Prediction of the MSCI EURO Index Based on Fuzzy Grammar Fragments Extracted from European Central Bank Statements. In Second International Conference of Soft Computing and Pattern Recongnition 2010 (SoCPaR 2010) (pp. 231-236). Paris.
  • Hogenboom, F.P., Milea, D.V., Frasincar, F. & Kaymak, U. (2010). Graphically Querying RDF Using RDF-GL. Dutch-Belgian Database Day 2010 (DBDBD 2010): Hasselt, Belgium (2010, november 22).
  • Hogenboom, A.C., Milea, D.V., Frasincar, F. & Kaymak, U. (2010). Optimizing RDF Chain Queries using Genetic Algorithms. Dutch-Belgian Database Day 2010 (DBDBD 2010): Hasselt, Belgium (2010, november 22 - 2010, november 22).
  • Kaymak, U., Ben-David, A. & Potharst, R. (2010). AUK: a simple alternative to the AUC. (ERIM Report Series Research in ManagementERS-2010-024-LIS ). 3000 DR Rotterdam: DEPARTMENT OF ECONOMETRICS.
  • Hogenboom, F.P., Frasincar, F. & Kaymak, U. (2010). Semantic Web-Based Knowledge Acquisition Using Key Events from News. In G. Danoy, M. Seredynski, R. Booth, B. Gateau, I. Jars & D. Khadraoui (Eds.), Proceedings of the Twenty-Second Benelux Conference on Artificial Intelligence (BNAIC 2010) (pp. 261-262). Luxembourg, Luxembourg: University of Luxembourg.
  • Hogenboom, F.P., Borgman, B., Frasincar, F. & Kaymak, U. (2010). Spatial Knowledge Representation on the Semantic Web. In Proceedings of the Fourth IEEE International Conference on Semantic Computing (ICSC 2010) (pp. 252-259). Pittsburgh, Pennsylvania, USA: IEEE Computer Society.
  • Hogenboom, A.C., Hogenboom, F.P., Kaymak, U., Ketter, W., Dalen, J. van & Collins, J. (2010). Towards a Dynamic Model of Supply Chain Regimes for Complex Multi-Agent Markets. In 2010 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2010) (pp. 3219-3225). Istanbul, Turkey: IEEE.
  • Hogenboom, A.C., Hogenboom, F.P., Kaymak, U., Wouters, P. & Jong, F.M.G. de (2010). Mining Economic Sentiment using Argumentation Structures. In J. Trujillo, D. Gillian, H. Kangassalo, S. Hartmann, M. Kirchberg, M. Rossi, I. Reinhartz-Berger, E. Zimányi & F. Frasincar (Eds.), Advances in Conceptual Modeling Applications and Challenges Vol. 6413. Lecture Notes in Computer Science (pp. 200-209). Berlin: Springer.
  • Hogenboom, F.P., Hogenboom, A.C., Frasincar, F., Kaymak, U., Meer, O. v.d., Schouten, K. & Vandic, D. (2010). SPEED: A Semantics-Based Pipeline for Economic Event Detection. In J. Parsons, M. Saeki, P. Shoval, C. Woo & Y. Wand (Eds.), Conceptual Modeling - ER 2010 Vol. 6412. Lecture Notes in Computer Science (pp. 452-457). Berlin: Springer.
  • Lovric, M., Kaymak, U. & Spronk, J. (2010). Modeling investor sentiment and overconfidence in an agent-based stock market. Human Systems Management, 29(2), 89-101.
  • Lovric, M., Kaymak, U. & Spronk, J. (2010). Modeling Loss Aversion and Biased Self-Attribution Using a Fuzzy Aggregation Operator. In Proceedings of the 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010) (pp. 1-8). Barcelona, Spain.
  • Frasincar, F., Milea, D.V. & Kaymak, U. (2010). tOWL: Integrating Time in OWL. In Roberto De Virgilio, Fausto Giunchiglia & Letizia Tanca (Eds.), Semantic Web Information Management: A Model-Based Perspective (pp. 225-246). Heidelberg: Springer.
  • Hogenboom, F.P., Frasincar, F. & Kaymak, U. (2010). An Overview of Approaches to Extract Information from Natural Language Corpora. In M. van der Heijden, M. Hinne, W. Kraaij, M. van Kuppeveld, S. Verberne & T. van der Weide (Eds.), Tenth Dutch-Belgian Information Retrieval Workshop (DIR 2010) (pp. 69-70). Nijmegen, The Netherlands.
  • Hogenboom, F.P., Milea, D.V., Frasincar, F. & Kaymak, U. (2010). RDF-GL: A SPARQL-Based Graphical Query Language for RDF. In R. Chbeir, Y. Badr, A. Abraham & A.-E. Hassanien (Eds.), Emergent Web Intelligence: Advanced Information Retrieval (Advanced Information and Knowledge Processing) (pp. 87-116). London: Springer.
  • Hogenboom, F.P., Frasincar, F. & Kaymak, U. (2010). A Review of Approaches for Representing RCC8 in OWL. In W. Chu, W.E. Wong, M.J. Palakal & C.-C. Hung (Eds.), Proceedings of the 2010 ACM Symposium on Applied Computing (SAC 2010) (pp. 1444-1445). Sierre, Switzerland: ACM.
  • Budai, G., Dekker, R. & Kaymak, U. (2009). Genetic and memetic algorithms for scheduling railway maintenance activities. (EI report serieEI 2009-30 ). 3000 DR Rotterdam: DEPARTMENT OF ECONOMETRICS.
  • Hogenboom, A.C., Ketter, W., Dalen, J. van, Kaymak, U., Collins, John & Gupta, Alok (2009). Adaptive Pricing in Multi-Agent Supply Chain Markets using Economic Regimes. In Conference on Information Systems and Technology (CIST 2009). San Diego, USA.
  • Tutmez, B., Tercan, A.E., Kaymak, U. & Lloyd, C.D. (2009). Local models for the analysis of spatially varying relationships in a lignite deposit. In D. Dubois, U. Kaymak, J.M.C. Sousa & J.P. Carvalho (Eds.), Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (pp. 351-356). Lisbon, Portugal.
  • Vieira, S.M., Sousa, J.M.C. & Kaymak, U. (2009). Feature selection using fuzzy objective functions. In D. Dubois, U. Kaymak, J.M.C. Sousa & J.P. Carvalho (Eds.), Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (pp. 1673-1678). Lisbon, Portugal.
  • Carvalho, J.P., Dubois, D., Kaymak, U. & Sousa, J.M.C. (Eds.). (2009). Final Program and Book of Abstracts of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference. Lisbon, Portugal: IFSA/EUSFLAT.
  • Carvalho, J.P., Dubois, D., Kaymak, U. & Sousa, J.M.C. (Eds.). (2009). Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference. Lisbon, Portugal: IFSA/EUSFLAT.
  • Lovric, M., Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Spronk, J. (2009). Modeling investor optimism with fuzzy connectives. In J.P. Carvalho, D. Dubois, U. Kaymak & J..M..C. Sousa (Eds.), Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (pp. 1803-1808). Lisbon, Portugal.
  • Milea, D.V., Frasincar, F. & Kaymak, U. (2009). A Temporal Web Ontology Language. (ERIM Report Series Research in ManagementERS-2009-050-LIS ). Rotterdam: Erasmus Research Institute of Management (ERIM).
  • Hogenboom, A.C., Milea, D.V., Frasincar, F. & Kaymak, U. (2009). Genetic Algorithms for RDF Chain Query Optimization. In T. Calders, K. Tuyls & M. Pechenizkiy (Eds.), Proceedings of the Twenty-First Benelux Conference on Artificial Intelligence (pp. 327-328). Eindhoven, The Netherlands.
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2009). Takagi Sugeno belief models. In Book fo Abstracts of the Third International conference on Computational and Financial Econometrics and Second Workshop of the ERCIM Working Group on Computing and Statistics (pp. 3-3). Limassol, Cyprus.
  • Hogenboom, A.C., Milea, D.V., Frasincar, F. & Kaymak, U. (2009). RCQ-GA: RDF Chain Query Optimization using Genetic Algorithms. In F. Buccafurri & T. di Noia (Eds.), Tenth International Conference on E-Commerce and Web Technologies Vol. 5692. Lecture Notes in Computer Science (pp. 181-192). Berlin: Springer.
  • Lovric, M., Kaymak, U. & Spronk, J. (2009). Overconfident investors in the LLS agent-based artificial financial market. In Proceedings of the IEEE Symposium on Computational Intelligence for Financial Engineering (CIFEr 2009) (pp. 58-65). Nashville, Tennessee, USA.
  • Lovric, M., Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Spronk, J. (2009). Modeling Investor Optimism with Fuzzy Connectives. In Proceedings of the IFSA World Congress (pp. 1803-1808). Lisbon.
  • Almeida e Santos Nogueira, R.J. de, Vieira, S.M., Milea, D.V., Kaymak, U. & Sousa, J.M.C. (2009). Knowledge discovery in the prediction of bankruptcy. In D. Dubois, U. Kaymak, J.M.C. Sousa & J.P. Carvalho (Eds.), Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (pp. 1785-1790). Lisbon, Portugal.
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2009). Tail point density estimation using probabilistics fuzzy systems. In J.P. Carvalho, D. Dubois, U. Kaymak & J.M.C. Sousa (Eds.), Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference (pp. 1809-1814). Lisbon, Portugal.
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2009). Probabilistic fuzzy systems in value-at-risk estimation. International Journal of Intelligent Systems in Accounting, Finance and Management, 16(1-2), 49-70.
  • Hogenboom, F.P., Ketter, W., Dalen, J. van, Kaymak, U., Collins, J. & Gupta, A. (2009). Economic Regime Identification and Prediction in TAC SCM Using Sales and Procurement Information. In E.H. Gerding (Ed.), Proceedings of the IJCAI'09 Workshop on Trading Agent Design and Analysis (TADA 2009) (pp. 25-34). Pasadena, California, USA.
  • Hogenboom, F.P., Ketter, W., Dalen, J. van, Kaymak, U., Collins, J. & Gupta, A. (2009). Identifying and Predicting Economic Regimes in Supply Chains Using Sales and Procurement Information. In Proceedings of the Eleventh International Conference on Electronic Commerce (ICEC 2009) (pp. 19-28). Taipei, Taiwan.
  • Hogenboom, A.C., Ketter, W., Dalen, J. van, Kaymak, U., Collins, J. & Gupta, A. (2009). Product Pricing in TAC SCM using Adaptive Real-Time Probability of Acceptance Estimations based on Economic Regimes. In Proceedings of the IJCAI'09 Workshop on Trading Agent Design and Analysis (TADA 2009) (pp. 15-24). Pasadena, California, USA.
  • Hogenboom, A.C., Ketter, W., Dalen, J. van, Kaymak, U., Collins, J. & Gupta, A. (2009). Product Pricing using Adaptive Real-Time Probability of Acceptance Estimations based on Economic Regimes. In Proceedings of the Eleventh International Conference on Electronic Commerce (ICEC 2009) (pp. 176-185). Taipei, Taiwan: ACM.
  • Hogenboom, F.P., Frasincar, F. & Kaymak, U. (2009). A Survey of Approaches on Mining the Structure from Unstructured Data. Dutch-Belgian Database Day 2009 (DBDBD 2009): Delft, The Netherlands (2009, november 30).
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2008). Value-at-risk estimation with fuzzy histograms. In Proceedings of the Eighth International Conference on Hybrid Intelligent Systems (HIS'08) (pp. 192-197). Barcelona, Spain.
  • Xu, D. & Kaymak, U. (2008). Value-at-risk estimation by using probabilistic fuzzy systems. In Proceedings of the 2008 IEEE International Conference on Fuzzy Systems (pp. 2109-2116). Hong Kong: IEEE.
  • Hinojosa, J, Nefti, S., Gray, J. & Kaymak, U. (2008). Reinforcement learning for multi-action probabilistic fuzzy controllers. EUCognition CogSys Doctoral Consortium: Munich, Germany (2008, juni 28 - 2008, juni 28).
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2008). Value-at-risk estimation with fuzzy histograms. III European Congress of Methodology (ECM 2008): Oviedo, Spain (2008, juli 08 - 2008, juli 12).
  • Almeida e Santos Nogueira, R.J. de, Kaymak, U. & Sousa, J.M.C. (2008). Fuzzy rule extraction from typicality and membership partitions. In Proceedings of the 2008 IEEE International Conference on Fuzzy Systems (pp. 1964-1970). Hong Kong: IEEE.
  • Almeida e Santos Nogueira, R.J. de & Kaymak, U. (2008). Value-at-risk estimation with fuzzy histograms. In Eight International Conference on Hybrid Intelligent Systems (pp. 192-197). 2008.
  • Hogenboom, A.C., Milea, D.V., Frasincar, F. & Kaymak, U. (2008). Genetic Algorithms for RFQ Query Path Optimization. In C. Guéret, P. Hitzler & S. Schlobach (Eds.), Proceedings of the First International Workshop on Nature Inspired Reasoning for the Semantic Web (pp. 16-30). Karlsruhe, Germany.
  • Milea, D.V., Frasincar, F. & Kaymak, U. (2008). The tOWL temporal web ontology language. In A. Nijholt, M. Pantic, M. Poel & H. Hondorp (Eds.), Proceedings of the 20th Belgian-Dutch Conference on Artificial Intelligence (BNAIC 2008) (pp. 343-344). Bad Boekelo, The Netherlands.
  • Micu, A., Mast, L., Milea, D.V., Frasincar, F. & Kaymak, U. (2008). Financial News Analysis Using a Semantic Web Approach. In A. Zilli, E. Damiani, P. Ceravolo, A. Corallo & G. Elia (Eds.), Knowledge Management: an Ontology-based Framework (pp. 311-328). Hershey, USA: IGI Global.
  • Hogenboom, F.P., Hogenboom, A.C., Gelder, R. van, Milea, D.V., Frasincar, F. & Kaymak, U. (2008). QMap: An RDF-Based Queryable World Map. In M. Naaranoja (Ed.), Proceedings of the Third International Conference on Knowledge Management in Organisations (KMO 2008) (pp. 99-110). Vaasa, Finland: Vaasan Yliopiston Julkaisuja.
  • Milea, D.V., Mrissa, M, Sluijs, K. van der & Kaymak, U. (2008). On temporal cardinality in the context of the TOWL language. In I.-Y. Song & M. Piattini et al. (Eds.), Advances in conceptual modeling-challenges and opportunities Vol. 5232. Lecture Notes in Computer Science (pp. 457-466). Berlin: Springer.
  • Milea, D.V., Frasincar, F. & Kaymak, U. (2008). Knowledge Engineering in a Temporal Semantic Web Context. In D. Schwabe, F. Curbera & P. Dantzig (Eds.), Eight International Conference en Web Engineering (ICWE'08) (pp. 65-74). Yorktown Height, New York, USA.
  • Lovric, M., Kaymak, U. & Spronk, J. (2008). A Conceptual Model of Investor Behavior. euCognition Cognitive Systems Doctoral Consortium: Munich, Germany (2008, juni 28 - 2008, juni 28).
  • Lovric, M., Kaymak, U. & Spronk, J. (2008). The Conceptual Model of Investor Behavior. (ERIM Report SeriesERS-2008-030-FA ). 3000 DR Rotterdam: ERIM.
  • Waltman, L.R. & Kaymak, U. (2008). Q-Learning agents in a Cournot oligopoly model. (EI-Reprint reeksEI-1484 ). 3000 DR Rotterdam: Econometrics.
  • Tutmez, B., Tercan, A.E. & Kaymak, U. (2008). An algorithm for quantifying regionalized ore grades. Journal of the South African Institute of Mining and Metallurgy, 108(2), 83-90.
  • Tutmez, B. & Kaymak, U. (2008). Fuzzy optimization of slab production from mechanical stone properties. Structural and Multidisciplinary Optimization, 37(1), 71-76.
  • Nefti, S., Oussalah, M. & Kaymak, U. (2008). A New Fuzzy Set Merging Technique Using Inclusion-Based Fuzzy Clustering. IEEE Transactions on Fuzzy Systems, 16(1), 145-161.
  • Waltman, L.R. & Kaymak, U. (2008). Q-learning agents in a Cournot oligopoly model. Journal of Economic Dynamics and Control, 32(10), 3275-3293.
  • Naso, D., Surico, M., Turchiano, B. & Kaymak, U. (2007). Genetic algorithms for supply-chain scheduling: a case study in the distribution of ready-mixed concrete. European Journal of Operational Research, 177(3), 2069-2099.
  • Sorban, K., Kaymak, U. & Spiering, J.W. (2007). From discrete-time models to continuous-time, asynchronous modeling of financial markets. Computational Intelligence, 23(2), 142-161.
  • Naso, D., Surico, M., Turchiano, B. & Kaymak, U. (2007). Genetic algorithms for supply-chain scheduling: a case study in the distribution of ready-mixed concrete. (EI reprint reeksEI-1448 ). 3000 DR Rotterdam: Econometrics.
  • Tutmez, B., Tercan, A.E. & Kaymak, U. (2007). Fuzzy modeling for reserve estimation based on spatial variability. Mathematical Geology, 39(1), 87-111.
  • Groenen, P.J.F., Kaymak, U. & Rosmalen, J.M. van (2007). Fuzzy clustering with Minkowski distance functions. In J Valente de Oliveira & W Pedrycz (Eds.), Advances in fuzzy clustering and its applications (pp. 53-68). Chicester: Wiley.
  • Soni, A., Eck, N.J.P. van & Kaymak, U. (2007). Prediction of stock price movements based on concept map information. In Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making (pp. 205-211).
  • Milea, D.V., Frasincar, F., Kaymak, U. & Noia, T. di (2007). An OWL-based approach towards representing time in web information systems. In Proceedings of the 4th Inernational Workshop on Web Information System Modelling (WISM 2007) and the 19th Conference on Advanced Information Systems Engineering (CAiSE'07) (pp. 791-802). Tapir Academic Press.
  • Mast, L., Micu, A., Frasincar, F., Milea, D.V. & Kaymak, U. (2007). StockWatcher - a semantic web application for custom selection of financial news. In KMO 2007.
  • Waltman, L.R. & Kaymak, U. (2007). A theoretical analysis at cooperative behavior in multi-agent Q-learning. In Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (pp. 84-91).
  • Sorban, K., Kaymak, U. & Spiering, J.W. (2007). From discrete-time models to continuous-time, asynchronous modeling of financial markets. In Proceedings of the 19th Belgian-Dutch conference on artificial intelligence (BNAIC'07) (pp. 317-318).
  • Tutmez, B. & Kaymak, U. (2007). Measure of uncertainty in regional grade variability. In P. Melin & O. Castillo (Eds.), Analysis and Design of Intelligent Systems Using Soft Computing Techniques (Advances in Soft Computing, 41) (pp. 511-518). Berlin: Springer.
  • Tutmez, B., Dag, A., Tercan, A.E. & Kaymak, U. (2007). Lignite thickness estimation via adaptive fuzzy-neural network. In C. Karpuz & M..A. Hindistan (Eds.), Proceedings of the 20th International Mining Congress and Exhibition of Turkey (IMCET 2007) (pp. 151-157). Ankara, Turkey.
  • Surico, M., Kaymak, U., Naso, D. & Dekker, R. (2007). A bi-objective evolutionary approach to robust scheduling. In Proceedings of the 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2007) (pp. 1632-1637). London, UK: IEEE.
  • Tongeren, T. van, Kaymak, U., Naso, D. & Asperen, E. van (2007). Q-learning in a competitive supply chain. In Proceedings of the 2007 IEEE International Conference on Systems, Man & Cybernetics (pp. 1211-1216). IEEE.
  • Otten, E. & Kaymak, U. (2007). Detecting suspicious accounting structures from XBRL reports. In V. Georgescu (Ed.), Proceedings of the XIV Congress of International Association for Fuzzy-Set Management and Economy (pp. 192-203). SIGEF.
  • Cheung, W.M. & Kaymak, U. (2007). A fuzzy logic based trading system. In Proceedings of the Third European Symposium on Nature-Inspired Smart Information Systems (pp. 141-148).
  • Milea, D.V., Frasincar, F., Kaymak, U. & Noia, T. di (2007). An OWL-based approach towards representing time in web information systems. In Proceedings of the 19th Belgian-Dutch conference on artificial intelligence (BNAIC'07) (pp. 381-382).
  • Mast, L., Micu, A., Frasincar, F., Milea, D.V. & Kaymak, U. (2007). Stock watcher a semantic web application for custom selection of financial news. In L. Uden, E. Damiani & G. Passiante (Eds.), Stock watcher a semantic web application for custom selection of financial news (pp. 1-6). Italy.
  • Groenen, P.J.F., Kaymak, U. & Rosmalen, J.M. van (2006). Fuzzy clustering with Minkowski distance functions. (Econometric Institute ReportEI 2006-24 ). 3000 DR Rotterdam: Econometrics.
  • Sorban, K., Kaymak, U. & Spiering, J.W. (2006). From discrete-time models to continuous-time, asynchronous modeling of financial markets. (ERIM Report Series Research in ManagementERS-2006-009-LIS ). 3000 DR Rotterdam: Econometrics.
  • Eck, N.J.P. van, Waltman, L.R., Berg, J. van den & Kaymak, U. (2006). Visualizing the computational intelligence field. IEEE Computational Intelligence Magazine, 1(4), 6-10.
  • Bosma, R.H., Phong, L.T., Kaymak, U., Berg, J. van den, Udo, H.M.J., Mensvoort, M.E.F. van & Tri, L.Q. (2006). Assessing and modelling farmers' decision making on integrating aquaculture into agriculture in the Mekong Delta. Njas-Wageningen Journal of Life Sciences, 53(3-4), 281-300.
  • Mendonca, L.F., Sousa, J.M.C., Kaymak, U. & Costa, J.M.G. Sa da (2006). Weighting goals and constraints in fuzzy predictive control. Journal of Intelligent & Fuzzy Systems, 17, 517-532.
  • Kaymak, U. (2006). Cognitive and smart adaptation in computer-communication networks. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 36(6), 1216-1217.
  • Tutmez, B., Hatipoglu, Z. & Kaymak, U. (2006). Modelling electrical conductivity of groundwater using and adaptive neuro-fuzzy inference system. Computers & Geosciences, 32, 421-433.
  • Larco Martinelli, J.A., Kaymak, U. & Dekker, R. (2006). Multi-objective scheduling for distributed security services. In Proceedings 2nd Annual Symposium NiSIS (Nature-Inspired Smart Information Systems) (pp. 141-148). Aachen: NiSIS Service Centre.
  • Eck, N.J.P. van, Waltman, L.R., Berg, J. van den & Kaymak, U. (2006). On the visualization of the soft computing knowledge domain. In E. Hullermeier, R. Kruse, A. Nurnberger & J. Strackeljan (Eds.), Proceedings of the symposium on fuzzy systems in computer science 2006. Magdeburg, Germany: Otto-von-Guericke University.
  • Faria, J.M., Silva, C.A., Sousa, J.M.C., Surico, M. & Kaymak, U. (2006). Distributed optimization using ant colony optimization in a concrete delivery supply chain. In Proceedings of the 2006 IEEE Congress on Evolutionary Computation. (pp. 380-387). Vancouver, Canada.
  • Surico, M., Kaymak, U., Naso, D. & Dekker, R. (2006). Hybrid meta-heuristics for robust scheduling. (ERIM Report Research in Management2006-018 ). 3000 DR Rotterdam: Econometrics.
  • Waltman, L.R. & Kaymak, U. (2006). A theoretical analysis of cooperative behavior in multi-agent Q-learning. (ERIM Report series research management2006-006-LIS ). 3000 DR Rotterdam: Econometrics.
  • Almeida e Santos Nogueira, R.J. de, Vieira, S.M., Sousa, J.M.C. & Kaymak, U. (2006). The prediction of bankruptcy using weighted fuzzy classifiers. In C.A. Mota Soares, J.A.C. Martins, H.C. Rodrigues, J.A.C. Ambrosio, C.A.B. Pina, C.M. Mota Soares, E.B.R. Pereira & J. Folgado (Eds.), Proceedings of the III European Conference on Computational Mechanics.. Lissabon/Portugal: Springer.
  • Bosma, R.H., Phong, L.T., Berg, J. van den, Kaymak, U., Udo, H.M.J. & Verreth, J.A.J. (2006). Using fuzzy logic to simulate the composition of farming systems in the Mekong Delta. In Proceedings of the 4th International Seminar on Tropical Animal Production. (pp. 484-494). Yogyakarta: Faculty of Animal Science Gadja Mada University.
  • Milea, D.V., Miedema, E., Berg, J. van den & Kaymak, U. (2006). Towards modelling traders' behavior. In F.B. Abdelaziz (Ed.), Proceedings of the XIII Congress of International Association for Fuzzy-set Management and Economy (pp. 161-170). Hammamet Tunisia: University of Tunis.
  • Eck, N.J.P. van, Waltman, L.R., Berg, J. van den & Kaymak, U. (2006). Visualizing the WCCI 2006 knowledge domain. In Proceedings of the 2006 IEEE International Conference on Fuzzy Systems (pp. 7862-7869). Vancouver, Canada.
  • Sorban, K., Bruin, A. de & Kaymak, U. (2005). On the Design of Artificial Stock Markets. (ERIM Report Series Research in Management2005-001 ). 3000 DR Rotterdam: Econometrics.
  • Sorban, K., Kaymak, U. & Bruin, A. de (2005). A Modular Agent-Based Environment for Studying Stock Markets. (ERIM Report Series Research in Management2005-017 ). 3000 DR Rotterdam: Econometrics.
  • Gelder, M.D. de, Kaymak, U., Sorban, K. & Asperen, E. van (2005). Minority games with asynchronous trading. In Proceedings Proceedings of the 2005 ICSC Congress on Computational Intelligence: Methods & Applications.
  • Waltman, L.R., Kaymak, U. & Berg, J. van den (2005). Maximum likelihood parameter estimation in probabilistic fuzzy classifiers. In Proceedings of the 2005 IEEE International Conference on Fuzzy Systems (pp. 1098-1103). Reno, Nevada, USA.
  • Kaymak, U., Dounias, G. & Thomaidis, N. (2005). Financial & managerial bench problems for nature-inspired intelligence. In NISIS Proceedings of the 2005 European symposium on nature inspired smart information system. Albufeira.
  • Waltman, L.R., Kaymak, U. & Berg, J. van den (2005). Fuzzy histograms: a statistical analysis. In Proceedings of Joint 4th EUSFLAT & 11th LFA Conference Proceedings of Joint 4th EUSFLAT & 11th LFA Conference (pp. 605-610). Barcelona/Spain.
  • Bosma, R.H., Kaymak, U., Berg, J. van den, Udo, H.M.J. & Verreth, J. (2005). Analysing Mekong delta farmers' motivations of aquaculture with fuzzy logic. In Abstract of the World Aquaculture 2005 Conference. Bali/Indonesia.
  • Duyvesteyn, K. & Kaymak, U. (2005). Genetic programming in economic modelling. In Proceedings Vol. 2. Proceedings of the 2005 IEEE Congress on Evolutionary computation (pp. 1025-1031). Edinburgh/Scotland.
  • Bosma, R., Kaymak, U., Berg, J. van den & Udo, H.M.J. (2005). Fuzzy modelling of farmer motivations for intergrated farming in the Vietnamese Mekong delta. In Proceedings of the 14th IEEE International Conference on Fuzzy Systems Proceedings of the 14th IEEE International Conference on Fuzzy Systems (pp. 827-832). Nevada/USA.
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2004). Financial markets analysis by using a probabilistic fuzzy modelling approach. International Journal of Approximate Reasoning, 35(3), 291-305.
  • Berg, J. van den & Kaymak, U. (2004). On the notion of statistical fuzzy entropy. In M. López-Diaz, M.A. Gil, P. Grzegorzewski, O. Hryniewicz & J. Lawry (Eds.), Soft methodology and random information systems (Advances in Soft Computing) (pp. 535-542). Berlin: Springer.
  • Kaymak, U. & Berg, J. van den (2004). On constructing probabilistic fuzzy classifiers from weighted fuzzy clustering. In Proceedings of the International Joint Conference on Neural Networks & IEEE International Conference on Fuzzy Systems, Budapest, Hungary (pp. 159-164).
  • Waltman, L.R. & Kaymak, U. (2004). Reinforcement learning in repeated Cournot oligopoly games. In M. Bausch, S. Faust, E-M. Lenart, S. Lieven & J. Wesbuer (Eds.), EUNITE 2004. European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems, June 10-12, Aachen, Germany (pp. 209-217). Aachen, Germay: EUNITE Service Center c/o ELITE Foundation.
  • Hamburger, Y., Kaymak, U. & Berg, J. van den (2004). Wavelet-based adaptation of value at risk estimation to different time horizons. In M. Bausch, S. Faust, E-M. Lenart, S. Lieven & J. Wesbuer (Eds.), European Symposium in Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems, June 10-12, Aachen, Germany (pp. 195-208). Aachen, Germany: EUNITE Service Center c/o ELITE Foundation.
  • Sorban, K., Polman, M.T.H., Bruin, A. de & Kaymak, U. (2004). An agent-based framework for artificial stock markets. In 16th Belgian-Dutch conference on artificial intelligence (BNAIC'04) (pp. 83-90). 2004.
  • Naso, D., Surico, M., Turchiano, B. & Kaymak, U. (2004). Genetic algorithms in supply chain scheduling of ready-mixed concrete. (ERIM Report Series Research in Management 2004096-LIS ). : .
  • Boer, K., Polman, M.T.H., Bruin, A. de & Kaymak, U. (2004). An agent-based framework for artificial stock markets. In R. Verbrugge, N. Taatgen & L. Schomaker (Eds.), Proceedings of the Sixteenth Belgium-Netherlands Conference on Artificial Intelligence (BNAIC), 21-22 October 2004 (pp. 83-90). Groningen: University of Groningen.
  • Naso, D., Surico, M., Turchiano, B. & Kaymak, U. (2004). Just-in-time production and delivery in supply chains: a hybrid evolutionary approach. In W. Thissen, P. Wierenga, M. Pantic & M. Ludema (Eds.), 2004 IEEE International Conference on Systems, Man & Cybernetics (pp. 1932-1937). Delft: TU Delft (Delft University of Technology).
  • Sorban, K., Bruin, A. de & Kaymak, U. (2004). Asynchronous role-based trading in a continuous artificial trading environment. In Fourth European Symposium on Intelligent Technologie and their implementation on Smart Adaptive Systems (EUNITE '04) (pp. 54-63). 2004.
  • Boer, K., Bruin, A. de & Kaymak, U. (2004). Asynchronous role-based trading in a continuous artificial trading environment. In M. Bausch, S. Faust, E-M. Lenart, S. Lieven & J. Wesbuer (Eds.), European Symposium in Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems, June 10-12, Aachen, Germany (pp. 54-63). Aachen, Germany: EUNITE Service Center c/o ELITE Foundation.
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2003). Financial markets analysis by probabilistic fuzzy modelling. (ERIM Report Series Research in Management 2003036-LIS ). : .
  • Sorban, K. & Kaymak, U. (2003). Microsimulation of artificial stock markets based on trader roles. In International Workshop on Data Mining and Adaptive Modelling Methods for Economics and Management (IWAMEM-03) (pp. 61-72). 2003.
  • Kaymak, U. & Sousa, J.M. (2003). Weighted constraint aggregation in fuzzy optimization. Constraints, 8(1), 29-46.
  • Cornelissen, A.M.G., Berg, J. van den, Koops, W.J. & Kaymak, U. (2003). Elicitation of expert knowledge for fuzzy evaluation of agricultural production systems. Agriculture, Ecosystems & Environment, 95(1), 1-18.
  • Cornelissen, A.M.G., Kaymak, U., Berg, J. van den & Koops, W.J. (2003). Transition interval estimation to elicit membership functions in fuzzy evaluation models of animal production systems. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp. 1200-1205). St.Louis, USA.
  • Kaymak, U., Bergh, W.M. van den & Berg, J. van den (2003). A fuzzy additive reasoning scheme for probabilistic Mamdani fuzzy systems. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp. 331-336).
  • Sousa, J.M., Madeira, S. & Kaymak, U. (2003). Modeling charity donations using target selection for revenue maximization. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp. 654-659). St.Louis, USA.
  • Mendonça, L.F., Sousa, J.M., Kaymak, U. & Sá da Costa, J.M. (2003). Fuzzy issues in multivariable predictive control. In Proceedings of the IEEE International Conference on Fuzzy Systems (pp. 506-511). St. Louis, USA.
  • Kaymak, U. (2003). Incremental feature selection for probabilistic fuzzy target selection. In Proceedings of the European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems Eunite 2003 (pp. 81-90).
  • Kaymak, U. & Berg, J. van den (2003). On probabilistic connections of fuzzy systems. In T. Heskes, P. Lucas, L. Vuurpijl & W. Wiegerinck (Eds.), Proceedings of the 15th Belgium-Netherlands Conference on Artificial Intelligence, October 23-24, 2003 (pp. 187-194). Nijmegen: University of Nijmegen.
  • Kaymak, U. (2003). Data and cluster weighting in target selection based on fuzzy clustering. Lecture Notes in Artificial Intelligence, 2715, 568-575.
  • Bandeira, L.P.C., Sousa, J.M.C. & Kaymak, U. (2003). Fuzzy clustering in classification using weighted features. Lecture Notes in Computer Science, 2715, 560-567.
  • Kaymak, U., Verkade, J.P. & Braake, H.A.B. te (2003). A heuristic lotting method for electronic reverse auctions. Lecture Notes in Computer Science, 2869, 322-329.
  • Boer, K. & Kaymak, U. (2003). Microsimulation of artificial stock markets based on trader roles. In P. Brazdil, M.L. Costa & L. Torgo (Eds.), International Workshop on Data Mining and Adaptive Modelling Methods for Economics and Management, 15-16 September (pp. 61-72). Porto - Portugal: IWAMEM.
  • Kaymak, U., Verkade, J.P. & Braake, H.A.B. te (2003). A lotting method for electronic reverse auctions. (ERIM Report Series Research in Management 2003042-LIS ). : .
  • Bergh, W.M. van den, Kaymak, U. & Berg, J. van den (2002). On the data-driven design of Takagi-Sugeno probabilistic fuzzy systems. In Vol. September. Proceedings of EUNITE 2002 (pp. 363-371).
  • Mendonça, L.F., Kaymak, U., Sousa, J.M. & Sá da Costa, J.M. (2002). Weighted criteria in multivariable fuzzy predictive control. In Proceedings 10th Mediterranean Conference on Control and Automation, Lisbon, Portugal (pp. 1-10).
  • Babuska, R., Veen, P.J. van der & Kaymak, U. (2002). Improved covariance estimation for gustafson-kessel clustering. In Proceedings of the 2002 IEEE International Conference on Fuzzy Systems (pp. 1081-1085).
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2002). Fuzzy classification using probability-based rule weighting. In Proceedings of the 2002 IEEE International Conference on Fuzzy Systems (pp. 991-996).
  • Sousa, J.M., Kaymak, U. & Madeira, S. (2002). A comparative study of fuzzy target selection methods in direct marketing. In Proceedings of the 2002 IEEE International Conference on Fuzzy Systems (pp. 1251-1256).
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2002). Probabilistic reasoning in fuzzy rule-based systems. In P. Grzegorzewski, O. Hryniewicz & M.Å. Gil (Eds.), Soft methods in probability, statistics and data analysis (Advances in Soft Computing) (pp. 189-196). Heidelberg: Physica Verlag.
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2002). Self-organizing maps, a visual exploration tool in datamining. In J. Mey (Ed.), Dealing with the data flood: mining data, ext and multimedia (pp. 298-307). Den Haag: STT/Beweton.
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2002). Probabilistic reasoning in fuzzy rule-based systems. In H. Blockeel & M. Denecker (Eds.), Proceedings of the Fourteenth Belgium-Netherlands Conference on Artificial Intelligence (BNAIC) , 21-22 October 2002, Leuven (pp. 11-18). Heidelberg: Physica Verlag.
  • Berg, J. van den, Kaymak, U. & Bergh, W.M. van den (2002). Fuzzy classification by using probability-based rule weighting. In M. Blockeel & M. Denecker (Eds.), Proceedings of the Fourtheenth Belgium-Netherlands Conference on Artificial Intelligence (BNAIC), 21-22 October 2002, Leuven (pp. 401-402). Heidelberg: Physica Verlag.
  • Cornelissen, A.M.G., Berg, J. van den, Koops, W.J. & Kaymak, U. (2002). Eliciting expert knowledge for fuzzy evaluation of agricultural production systems. (ERIM Report Series Research in Management 2002108-LIS ). : .
  • Kaymak, U. & Setnes, M. (2002). Fuzzy clustering with volume prototypes and adaptive cluster merging. IEEE Transactions on Fuzzy Systems, 10(6), 705-712.
  • Sousa, J.M. & Kaymak, U. (2002). Fuzzy decision making in modeling and control (World Scientific Series in Robotics and Intelligent Systems, 27). River Edge, New Jersey: World Scientific Publishing Co. Pte.Ltd..
  • Potharst, R., Kaymak, U. & Pijls, W.H.L.M. (2002). Neural networks for target selection in direct marketing. In K. Smith & J. Gupta (Eds.), Neural networks in business: Techniques and applications (pp. 89-110). Hershey, Pennsylvania, USA: Idea Group Publishing.
  • Bruin, A. de & Kaymak, U. (). From algorithms to models of economic phenomena, 10 pag. ERIM Conference: Rotterdam (2001, november 16).
  • Kaymak, U., Tseng, J.C.M., Kort, B. de & Oosterhout, M.P.A. van (2001). Collaborative e-business scenarios. (GigaPort Virtuele HavenT2.D5 ). : .
  • Berg, J. van den, Bergh, W.M. van den & Kaymak, U. (2001). Detecting noise trading using fuzzy exception learning. In Proceedings of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference (pp. 946-951).
  • Berg, J. van den, Bergh, W.M. van den & Kaymak, U. (2001). Fuzzy exception learning for noise trading unmasking. In The European Operational Research Conference 2001 (pp. 103-104).
  • Berg, J. van den, Bergh, W.M. van den & Kaymak, U. (2001). Detecting noice trading using fuzzy exception learning. In Proceedings of the 13th Belgian-Netherlands Conference on Artificial Intelligence 2001 (pp. 337-338).
  • Potharst, R., Kaymak, U. & Pijls, W.H.L.M. (2001). Neural networks for target selection in direct marketing. (ERIM Report Series in Management, March 200114-LIS ). : .
  • Pijls, W.H.L.M., Potharst, R. & Kaymak, U. (2001). Pattern-based target selection applied to fund raising. (ERIM Report Series in Management, October 200156-LIS ). : .
  • Kaymak, U. & Sousa, J.M. (2001). Weighted constraints in fuzzy optimization. (ERIM Report Series in Management, March 200119-LIS ). : .
  • Pijls, W.H.L.M., Potharst, R. & Kaymak, U. (2001). Pattern-based target selection applied to fund raising. In B. Kröse, M. de Rijke, G. Schreiber & M. van Someren (Eds.), Proceedings of the 13th Belgium-Netherlands Conference on Artificial Intelligence (pp. 211-218). Amsterdam: Rode Hoed.
  • Kaymak, U. & Sousa, J.M. (2001). Model predictive control using fuzzy decision functions. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 31(1), 54-65.
  • Kaymak, U. & Setnes, M. (2001). Fuzzy modeling of client preference from large data sets: An application to target selection in direct marketing. IEEE Transactions on Fuzzy Systems, 9(1), 153-163.
  • Pijls, W.H.L.M., Potharst, R. & Kaymak, U. (2001). Pattern-based target selection applied to fund raising. In W. Gersten & K. Vanhoof (Eds.), Data mining for marketing applications (12th European Conference on Machine Learning (ECML'01) and 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'01), September 7th (pp. 15-24). Freiburg, Germany: ECML/PKDD-01 Workshop.
  • Kaymak, U. (2001). Fuzzy target selection using RFM variables. In Proceedings of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference (pp. 1038-1043).
  • Kaymak, U. & Setnes, M. (2001). Fuzzy clustering for target selection in direct marketing. In Abstracts of the European Operational Research Conference (pp. 103-103).
  • Boer, K. & Kaymak, U. (2001). Adaption in agent-based systems. In Proceedings of the 13th Belgian-Netherlands Conference on Artificial Intelligence 2001 (pp. 347-354).
  • Kaymak, U., Potharst, R. & Pijls, W.H.L.M. (2001). Selecting targets for a charity organization by using neural networks. In Abstracts of the European Operational Research Conference (pp. 103-103).
  • Kaymak, U., Berkel, J.P. van, Kulawski, G., Weisenborn, T. & White, M. (2001). Gas field planning tool. Netherlands Journal of Geosciences. Geologie en Mijnbouw, 80(1), 103-105.
  • Kaymak, U. & Boer, K. (2001). An agent-based taxonomy of adaption in computional economics. In Proceedings of EUNITE 2001 (pp. 379-385).
  • Kaymak, U. & Sousa, J.M. (2001). Weighting of constraints in fuzzy optimization. In Vol. 3. Proceedings of the 10th IEEE International Conference on Fuzzy Systems (pp. 1131-1134).
  • Bergh, W.M. van den, Berg, J. van den & Kaymak, U. (2001). Probabilistic and statistical fuzzy set foundations of competitive exception learning. (ERIM Report Series Research in Management 2001 (ERS)40-LIS ). : .
  • Bergh, W.M. van den, Berg, J. van den & Kaymak, U. (2001). Probabilistic and statistical fuzzy set foundations of competitive exception learning. In x xx (Ed.), Proceedings of the 10th IEEE international conference on fuzzy systems (pp. 1035-1038). Melbourne, Australia: IEEE Computer Society Press.
  • Berg, J. van den, Bergh, W.M. van den & Kaymak, U. (2001). Probabilistic and statistical fuzzy set foundations of competitive exception learning. (ERIM Report Series in Management, July 200140-LIS ). : .
  • Kaymak, U. & Setnes, M. (2000). Fuzzy clustering based target selection. In A. van den Bosch & H. Weigand (Eds.), Proceedings of the Twelfth BNAIC (pp. 109-116). Amsterdam: A.
  • Kaymak, U. (2000). A unified approach for practical applications of fuzzy clustering. In A. van den Bosch & H. Weigand (Eds.), Proceedings of the Twelfth BNAI Conference, November 2000 (pp. 101-108). Tilburg: Katholieke Universiteit Brabant.
  • Kaymak, U. & Setnes, M. (2000). Fuzzy modeling of client preference in data-rich marketing environments. (ERS49-LIS ). : .
  • Kaymak, U. & Setnes, M. (2000). Extended fuzzy clustering algorithms. (ERIM Report Series Research in Management51-LIS ). : .
  • Kaymak, U. & Setnes, M. (2000). Target selection based on fuzzy clustering: a volume prototype approach to CoIL Challenge 2000. (Technical Report2000-09 ). Leiden: Leiden Institute of Advanced Computer Science.
Professional publications (1)
  • Kaymak, U. (2006). An MSc program in computational economics with a focus on computational intelligence. IEEE Computational Intelligence Magazine, 1(2), 41-41.
Other output (1)
  • Kaymak, U. (2009). The Information Metamorphosis in Economics. Oratie (2009, maart 06). Rotterdam: Erasmus Universiteit.