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ORCIDRichard Weber 0002
Person information
- affiliation: Universidad de Chile, Department of Industrial Ingeneering, Chile
- affiliation: MIT GmbH, Aachen, Germany
- affiliation (PhD 1992): RWTH Aachen University, Institut für Wirtschaftswissenschaften, Germany
Other persons with the same name
- Richard Weber — disambiguation page
- Richard Weber 0001 — Dresden University of Technology, Institute of Traffic Telematics, Germany
- Richard R. Weber 0003
![[0000-0002-2336-5534]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-2336-5534")
(aka: Richard Weber 0003) — University of Cambridge, Department of Mathematics, UK
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2020 – today
- 2024
[j48]Koen W. De Bock, Kristof Coussement, Arno De Caigny, Roman Slowinski, Bart Baesens, Robert N. Boute, Tsan-Ming Choi, Dursun Delen, Mathias Kraus, Stefan Lessmann, Sebastián Maldonado, David Martens, María Óskarsdóttir, Carla Vairetti, Wouter Verbeke, Richard Weber:
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. Eur. J. Oper. Res. 317(2): 249-272 (2024)- [j47]Ramiro Saltos, Richard Weber, Dayana Saltos:
FuSVC: A New Labeling Rule for Support Vector Clustering Using Fuzzy Sets. IEEE Trans. Fuzzy Syst. 32(10): 5777-5790 (2024) - 2023
- [j46]Renny Márquez, Richard Weber:
Dynamic community detection including node attributes. Expert Syst. Appl. 223: 119791 (2023) - [j45]Ramiro Saltos, Richard Weber:
Generalized black hole clustering algorithm. Pattern Recognit. Lett. 176: 196-201 (2023) - 2022
- [j44]Ramiro Saltos Atiencia, Richard Weber:
Rough-Fuzzy Support Vector Clustering with OWA Operators. Inteligencia Artif. 25(69): 42-56 (2022) - 2020
- [j43]Fredy Troncoso, Richard Weber:
A novel approach to detect associations in criminal networks. Decis. Support Syst. 128 (2020) - [j42]Fredy Troncoso, Richard Weber:
Integrating relations and criminal background to identifying key individuals in crime networks. Decis. Support Syst. 139: 113405 (2020) - [j41]Sebastián Maldonado, Georg Peters, Richard Weber:
Credit scoring using three-way decisions with probabilistic rough sets. Inf. Sci. 507: 700-714 (2020)
2010 – 2019
- 2019
- [c26]Renny Márquez, Richard Weber, André C. P. L. F. de Carvalho:
A non-negative matrix factorization approach to update communities in temporal networks using node features. ASONAM 2019: 728-732 - [c25]Renny Márquez, Richard Weber:
Overlapping Community Detection in Static and Dynamic Social Networks. WSDM 2019: 822-823 - 2018
- [j40]Jaime Miranda, Pablo A. Rey, Antoine Sauré, Richard Weber:
Metro Uses a Simulation-Optimization Approach to Improve Fare-Collection Shift Scheduling. Interfaces 48(6): 529-542 (2018) - [j39]José M. Merigó, Witold Pedrycz, Richard Weber, Catalina de la Sotta:
Fifty years of Information Sciences: A bibliometric overview. Inf. Sci. 432: 245-268 (2018) - [j38]Georg Peters, Richard Weber:
dynXcube - Categorizing dynamic data analysis. Inf. Sci. 463-464: 21-32 (2018) - [c24]Ramiro Saltos Atiencia, Richard Weber:
Dynamic Rough-Fuzzy Support Vector Domain Description for Outlier Detection. FUZZ-IEEE 2018: 1-8 - 2017
- [j37]Richard Weber, Cristián Bravo, Rudolf Kruse, Sebastián Maldonado:
Special issue "Applied soft computing for business analytics". Appl. Soft Comput. 60: 750-751 (2017) - [j36]Nicolás Figueroa, Gaston L'Huillier, Richard Weber:
Adversarial classification using signaling games with an application to phishing detection. Data Min. Knowl. Discov. 31(1): 92-133 (2017) - [j35]Ramiro Saltos, Richard Weber, Sebastián Maldonado:
Dynamic Rough-Fuzzy Support Vector Clustering. IEEE Trans. Fuzzy Syst. 25(6): 1508-1521 (2017) - 2016
- [j34]Ramiro Saltos Atiencia, Richard Weber:
A Rough-Fuzzy approach for Support Vector Clustering. Inf. Sci. 339: 353-368 (2016) - 2015
- [j33]Sebastián Maldonado, Álvaro Flores, Thomas Verbraken, Bart Baesens, Richard Weber:
Profit-based feature selection using support vector machines - General framework and an application for customer retention. Appl. Soft Comput. 35: 740-748 (2015) - [j32]Sebastián Maldonado, Ricardo Montoya, Richard Weber:
Advanced conjoint analysis using feature selection via support vector machines. Eur. J. Oper. Res. 241(2): 564-574 (2015) - [j31]Sebastián Maldonado, Emilio Carrizosa, Richard Weber:
Kernel Penalized K-means: A feature selection method based on Kernel K-means. Inf. Sci. 322: 150-160 (2015) - [j30]Cristián Bravo, Lyn C. Thomas, Richard Weber:
Improving credit scoring by differentiating defaulter behaviour. J. Oper. Res. Soc. 66(5): 771-781 (2015) - [j29]Vadim V. Strijov, Gerhard-Wilhelm Weber, Richard Weber, Süreyya Özögür-Akyüz:
Editorial of the special issue data analysis and intelligent optimization with applications. Mach. Learn. 101(1-3): 1-4 (2015) - [c23]Ramiro Saltos Atiencia, Richard Weber Haas:
Rough-Fuzzy Support Vector Domain Description for outlier detection. FUZZ-IEEE 2015: 1-6 - 2014
- [j28]Thomas Verbraken, Cristián Bravo, Richard Weber, Bart Baesens:
Development and application of consumer credit scoring models using profit-based classification measures. Eur. J. Oper. Res. 238(2): 505-513 (2014) - [j27]Sebastián Maldonado, Juan Pérez, Richard Weber, Martine Labbé:
Feature selection for Support Vector Machines via Mixed Integer Linear Programming. Inf. Sci. 279: 163-175 (2014) - [j26]Sebastián Maldonado, Richard Weber, Fazel Famili:
Feature selection for high-dimensional class-imbalanced data sets using Support Vector Machines. Inf. Sci. 286: 228-246 (2014) - 2013
- [j25]Cristián Bravo, Sebastián Maldonado, Richard Weber:
Granting and managing loans for micro-entrepreneurs: New developments and practical experiences. Eur. J. Oper. Res. 227(2): 358-366 (2013) - [j24]Georg Peters, Fernando A. Crespo, Pawan Lingras, Richard Weber:
Soft clustering - Fuzzy and rough approaches and their extensions and derivatives. Int. J. Approx. Reason. 54(2): 307-322 (2013) - [j23]Nelson Devia, Richard Weber:
Generating crime data using agent-based simulation. Comput. Environ. Urban Syst. 42: 26-41 (2013) - 2012
- [j22]Georg Peters, Richard Weber, René Nowatzke:
Dynamic rough clustering and its applications. Appl. Soft Comput. 12(10): 3193-3207 (2012) - [j21]Georg Peters, Richard Weber:
Dynamic clustering with soft computing. WIREs Data Mining Knowl. Discov. 2(3): 226-236 (2012) - 2011
- [j20]Donald E. Brown, Fazel Famili, Gerhard Paass, Kate Smith-Miles, Lyn C. Thomas, Richard Weber, Ricardo Baeza-Yates, Cristián Bravo, Gaston L'Huillier, Sebastián Maldonado:
Future trends in business analytics and optimization. Intell. Data Anal. 15(6): 1001-1017 (2011) - [j19]Georg Peters, Richard Weber:
A class of dynamic rough partitive algorithms. Int. J. Intell. Syst. 26(6): 540-554 (2011) - [j18]Sebastián Maldonado, Richard Weber, Jayanta Basak:
Simultaneous feature selection and classification using kernel-penalized support vector machines. Inf. Sci. 181(1): 115-128 (2011) - [c22]Sebastián Maldonado, Richard Weber:
Embedded Feature Selection for Support Vector Machines: State-of-the-Art and Future Challenges. CIARP 2011: 304-311 - [c21]Cristián Bravo, Richard Weber:
Semi-supervised Constrained Clustering with Cluster Outlier Filtering. CIARP 2011: 347-354 - 2010
- [j17]Jose Guajardo, Richard Weber, Jaime Miranda:
A model updating strategy for predicting time series with seasonal patterns. Appl. Soft Comput. 10(1): 276-283 (2010) - [c20]Georg Peters, Richard Weber, Fernando A. Crespo:
Uncertainty modeling in dynamic clustering - A soft computing perspective. FUZZ-IEEE 2010: 1-6 - [c19]Cristián Bravo, Nicolás Figueroa, Richard Weber:
Game Theory & Data Mining model for price dynamics in financial institutions. IJCNN 2010: 1-8 - [c18]Sebastián Maldonado, Richard Weber:
Feature selection for support vector regression via Kernel penalization. IJCNN 2010: 1-7 - [c17]Cristián Bravo, Nicolás Figueroa, Richard Weber:
Modeling Pricing Strategies Using Game Theory and Support Vector Machines. ICDM 2010: 323-337 - [c16]Gaston L'Huillier, Alejandro Hevia, Richard Weber, Sebastián A. Ríos:
Latent semantic analysis and keyword extraction for phishing classification. ISI 2010: 129-131
2000 – 2009
- 2009
- [j16]Sebastián Maldonado, Richard Weber:
A wrapper method for feature selection using Support Vector Machines. Inf. Sci. 179(13): 2208-2217 (2009) - [j15]Gaston L'Huillier, Richard Weber, Nicolás Figueroa:
Online phishing classification using adversarial data mining and signaling games. SIGKDD Explor. 11(2): 92-99 (2009) - [c15]Gaston L'Huillier, Richard Weber, Nicolás Figueroa:
Online phishing classification using adversarial data mining and signaling games. KDD Workshop on CyberSecurity and Intelligence Informatics 2009: 33-42 - 2008
- [j14]Witold Pedrycz, Richard Weber:
Special issue on soft computing for dynamic data mining. Appl. Soft Comput. 8(4): 1281-1282 (2008) - [j13]Georg Peters, Martin Lampart, Richard Weber:
Evolutionary Rough k-Medoid Clustering. Trans. Rough Sets 8: 289-306 (2008) - [c14]Cristián Bravo, Jose Luis Lobato, Richard Weber, Gaston L'Huillier:
A Hybrid System for Probability Estimation in Multiclass Problems Combining SVMs and Neural Networks. HIS 2008: 649-654 - [c13]Georg Peters, Richard Weber:
A Dynamic Approach to Rough Clustering. RSCTC 2008: 379-388 - [c12]Georg Peters, Roger Tagg, Richard Weber:
An Application of Rough Set Concepts to Workflow Management. RSKT 2008: 715-722 - 2007
- [j12]Luis Aburto, Richard Weber:
Improved supply chain management based on hybrid demand forecasts. Appl. Soft Comput. 7(1): 136-144 (2007) - [c11]Luis Aburto, Richard Weber:
A Sequential Hybrid Forecasting System for Demand Prediction. MLDM 2007: 518-532 - 2006
- [j11]Jose Guajardo, Richard Weber, Jaime Miranda:
A Forecasting Methodology Using Support Vector Regression and Dynamic Feature Selection. J. Inf. Knowl. Manag. 5(4): 329-335 (2006) - [c10]Sven F. Crone, Jose Guajardo, Richard Weber:
The Impact of Preprocessing on Support Vector Regression and Neural Networks in Time Series Prediction. DMIN 2006: 37-44 - [c9]Sven F. Crone, Jose Guajardo, Richard Weber:
A study on the ability of Support Vector Regression and Neural Networks to Forecast Basic Time Series Patterns. IFIP AI 2006: 149-158 - 2005
- [j10]Fernando A. Crespo, Richard Weber:
A methodology for dynamic data mining based on fuzzy clustering. Fuzzy Sets Syst. 150(2): 267-284 (2005) - [j9]Juan D. Velásquez, Richard Weber, Hiroshi Yasuda, Terumasa Aoki:
Acquisition and Maintenance of Knowledge for Online Navigation Suggestions. IEICE Trans. Inf. Syst. 88-D(5): 993-1003 (2005) - [c8]Jose Guajardo, Jaime Miranda, Richard Weber:
A Hybrid Forecasting Methodology using Feature Selection and Support Vector Regression. HIS 2005: 341-346 - [c7]Jaime Miranda, Ricardo Montoya, Richard Weber:
Linear Penalization Support Vector Machines for Feature Selection. PReMI 2005: 188-192 - 2004
- [j8]Sandro Araya, Mariano Silva, Richard Weber:
A methodology for web usage mining and its application to target group identification. Fuzzy Sets Syst. 148(1): 139-152 (2004) - [j7]Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber:
A New Similarity Measure to Understand Visitor Behavior in a Web Site. IEICE Trans. Inf. Syst. 87-D(2): 389-396 (2004) - [c6]Juan D. Velásquez, Richard Weber, Hiroshi Yasuda, Terumasa Aoki:
A Methodology to Find Web Site Keywords. EEE 2004: 285-292 - 2003
- [j6]Ana María Angel, Luis Alberto Taladriz, Richard Weber:
Soquimich Uses a System Based on Mixed-Integer Linear Programming and Expert Systems to Improve Customer Service. Interfaces 33(4): 41-52 (2003) - [c5]Daniel Schwartz, Kate A. Smith, Leonid Churilov, Michael Dally, Richard Weber:
Improving Risk Grouping Rules for Prostate Cancer Patients Using Self-Organizing Maps. HIS 2003: 126-136 - [c4]Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber, Eduardo S. Vera:
Using Self Organizing Feature Maps to Acquire Knowledge about Visitor Behavior in a Web Site. KES 2003: 951-958 - [c3]Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber:
Using the KDD Process to Support Web Site Reconfigurations. Web Intelligence 2003: 511-515 - 2002
- [c2]Sandro Araya, Mariano Silva, Richard Weber:
Identifying web usage behavior of bank customers. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2002: 245-251 - [c1]Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki, Richard Weber:
Voice Codification using Self Organizing Maps as Data Mining Tool. HIS 2002: 480-489 - 2000
- [j5]P. Hofmeister, Arno Joentgen, Lara Mikenina, Richard Weber, Hans-Jürgen Zimmermann:
Komplexitätsreduktion in der Szenarioanalyse mit Hilfe dynamischer Fuzzy-Datenanalyse. OR Spectr. 22(3): 403-420 (2000)
1990 – 1999
- 1999
- [j4]Arno Joentgen, Lara Mikenina, Richard Weber, Hans-Jürgen Zimmermann:
Dynamic fuzzy data analysis based on similarity between functions. Fuzzy Sets Syst. 105(1): 81-90 (1999) - [j3]Arno Joentgen, Lara Mikenina, Richard Weber, A. Zeugner, Hans-Jürgen Zimmermann:
Automatic fault detection in gearboxes by dynamic fuzzy data analysis. Fuzzy Sets Syst. 105(1): 123-132 (1999) - 1997
- [j2]Fazel Famili, Wei-Min Shen, Richard Weber, Evangelos Simoudis:
Data Preprocessing and Intelligent Data Analysis. Intell. Data Anal. 1(1-4): 3-23 (1997) - 1992
- [b1]Richard Weber:
Entwicklung und Anwendung von Verfahren zur automatischen Akquisition unsicheren Wissens. RWTH Aachen University, Germany, VDI-Verlag 1992, ISBN 978-3-18-141110-0, pp. 1-224 - 1991
- [j1]Richard Weber, Hans-Jürgen Zimmermann:
Automatische Akquisition von unscharfem Expertenwissen. Künstliche Intell. 5(2): 20-26 (1991)
Coauthor Index
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