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ORCIDChris Cornelis
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- affiliation: Ghent University, Belgium
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2020 – today
- 2023
[j72]Nicolás Madrid
, Chris Cornelis:
Kitainik axioms do not characterize the class of inclusion measures based on contrapositive fuzzy implications. Fuzzy Sets Syst. 456: 208-214 (2023)- [j71]Adnan Theerens, Chris Cornelis:
Fuzzy rough sets based on fuzzy quantification. Fuzzy Sets Syst. 473: 108704 (2023) - [j70]JingTao Yao, Chris Cornelis, Guoyin Wang, Yiyu Yao:
Uncertainty and three-way decision in data science. Int. J. Approx. Reason. 162: 109024 (2023) - [j69]Olha Kaminska, Chris Cornelis, Véronique Hoste:
Fuzzy rough nearest neighbour methods for detecting emotions, hate speech and irony. Inf. Sci. 625: 521-535 (2023) - [j68]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Granular approximations: A novel statistical learning approach for handling data inconsistency with respect to a fuzzy relation. Inf. Sci. 629: 249-275 (2023) - [c71]Chris Cornelis, Henri Bollaert:
Combination of Fuzzy Sets and Rough Sets for Machine Learning Purposes (Tutorial Lecture - Extended Abstract). FedCSIS 2023: 67 - [i14]Oliver Urs Lenz, Chris Cornelis:
Classifying token frequencies using angular Minkowski p-distance. CoRR abs/2309.14495 (2023) - [i13]Oliver Urs Lenz, Henri Bollaert, Chris Cornelis:
A unified weighting framework for evaluating nearest neighbour classification. CoRR abs/2311.16872 (2023) - 2022
- [j67]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Granular representation of OWA-based fuzzy rough sets. Fuzzy Sets Syst. 440: 112-130 (2022) - [j66]Adnan Theerens, Oliver Urs Lenz, Chris Cornelis:
Choquet-based fuzzy rough sets. Int. J. Approx. Reason. 146: 62-78 (2022) - [j65]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Optimised one-class classification performance. Mach. Learn. 111(8): 2863-2883 (2022) - [c70]Chris Cornelis:
Hybridization of Fuzzy Sets and Rough Sets: Achievements and Opportunities. FedCSIS 2022: 7-14 - [c69]Adnan Theerens, Chris Cornelis:
Fuzzy Quantifier-Based Fuzzy Rough Sets. FedCSIS 2022: 269-278 - [c68]Oliver Urs Lenz, Chris Cornelis, Daniel Peralta:
Fuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification. FUZZ-IEEE 2022: 1-8 - [c67]Olha Kaminska, Chris Cornelis, Véronique Hoste:
LT3 at SemEval-2022 Task 6: Fuzzy-Rough Nearest Neighbor Classification for Sarcasm Detection. SemEval@NAACL 2022: 987-992 - [i12]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Multi-class granular approximation by means of disjoint and adjacent fuzzy granules. CoRR abs/2202.07584 (2022) - [i11]Adnan Theerens, Oliver Urs Lenz, Chris Cornelis:
Choquet-Based Fuzzy Rough Sets. CoRR abs/2202.10872 (2022) - [i10]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Fuzzy granular approximation classifier. CoRR abs/2206.01240 (2022) - [i9]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
No imputation without representation. CoRR abs/2206.14254 (2022) - [i8]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Representing missing values through polar encoding. CoRR abs/2210.01905 (2022) - [i7]Henri Bollaert, Chris Cornelis:
Evaluation of the impact of the indiscernibility relation on the fuzzy-rough nearest neighbours algorithm. CoRR abs/2211.14134 (2022) - [i6]Adnan Theerens, Chris Cornelis:
Fuzzy Rough Sets Based on Fuzzy Quantification. CoRR abs/2212.04327 (2022) - 2021
- [j64]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Fuzzy extensions of the dominance-based rough set approach. Int. J. Approx. Reason. 129: 1-19 (2021) - [j63]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Average Localised Proximity: A new data descriptor with good default one-class classification performance. Pattern Recognit. 118: 107991 (2021) - [c66]Mauricio Restrepo, Chris Cornelis:
Attribute Reduction Using Functional Dependency Relations in Rough Set Theory. IJCRS 2021: 90-96 - [c65]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Adapting Fuzzy Rough Sets for Classification with Missing Values. IJCRS 2021: 192-200 - [c64]Olha Kaminska, Chris Cornelis, Véronique Hoste:
Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets. IJCRS 2021: 231-246 - [c63]Olha Kaminska, Chris Cornelis, Véronique Hoste:
Nearest neighbour approaches for Emotion Detection in Tweets. WASSA@EACL 2021: 203-212 - [e5]Sheela Ramanna, Chris Cornelis, Davide Ciucci:
Rough Sets - International Joint Conference, IJCRS 2021, Bratislava, Slovakia, September 19-24, 2021, Proceedings. Lecture Notes in Computer Science 12872, Springer 2021, ISBN 978-3-030-87333-2 [contents] - [i5]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Average Localised Proximity: a new data descriptor with good default one-class classification performance. CoRR abs/2101.11037 (2021) - [i4]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Optimised one-class classification performance. CoRR abs/2102.02618 (2021) - [i3]Olha Kaminska, Chris Cornelis, Véronique Hoste:
Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets. CoRR abs/2107.05392 (2021) - [i2]Olha Kaminska, Chris Cornelis, Véronique Hoste:
Nearest neighbour approaches for Emotion Detection in Tweets. CoRR abs/2107.05394 (2021) - [i1]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
A Novel Machine Learning Approach to Data Inconsistency with respect to a Fuzzy Relation. CoRR abs/2111.13447 (2021) - 2020
- [j62]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Scalable Approximate FRNN-OWA Classification. IEEE Trans. Fuzzy Syst. 28(5): 929-938 (2020) - [c62]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Rough Sets Meet Statistics - A New View on Rough Set Reasoning About Numerical Data. IJCRS 2020: 78-92 - [c61]Mauricio Restrepo, Chris Cornelis:
Attribute Reduction from Closure Operators and Matroids in Rough Set Theory. IJCRS 2020: 183-192 - [c60]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
fuzzy-rough-learn 0.1: A Python Library for Machine Learning with Fuzzy Rough Sets. IJCRS 2020: 491-499
2010 – 2019
- 2019
- [j61]Lynn D'eer, Chris Cornelis:
Decision reducts and bireducts in a covering approximation space and their relationship to set definability. Int. J. Approx. Reason. 109: 42-54 (2019) - [j60]Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys:
Weight selection strategies for ordered weighted average based fuzzy rough sets. Inf. Sci. 501: 155-171 (2019) - [c59]Marko Palangetic, Chris Cornelis, Salvatore Greco, Roman Slowinski:
Extension of the Fuzzy Dominance-Based Rough Set Approach Using Ordered Weighted Average Operators. EUSFLAT Conf. 2019 - [c58]Mauricio Restrepo, Chris Cornelis:
Rough Matroids Based on Dual Approximation Operators. IJCRS 2019: 118-129 - [c57]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
A Scalable Approach to Fuzzy Rough Nearest Neighbour Classification with Ordered Weighted Averaging Operators. IJCRS 2019: 197-209 - 2018
- [j59]Lynn D'eer, Chris Cornelis:
A comprehensive study of fuzzy covering-based rough set models: Definitions, properties and interrelationships. Fuzzy Sets Syst. 336: 1-26 (2018) - [j58]Sarah Vluymans, Chris Cornelis, Francisco Herrera, Yvan Saeys:
Multi-label classification using a fuzzy rough neighborhood consensus. Inf. Sci. 433-434: 96-114 (2018) - [j57]Sarah Vluymans, Alberto Fernández, Yvan Saeys, Chris Cornelis, Francisco Herrera:
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach. Knowl. Inf. Syst. 56(1): 55-84 (2018) - 2017
- [j56]Lynn D'eer, Chris Cornelis, Lluís Godo:
Fuzzy neighborhood operators based on fuzzy coverings. Fuzzy Sets Syst. 312: 17-35 (2017) - [j55]Lynn D'eer, Chris Cornelis:
Notes on covering-based rough sets from topological point of view: Relationships with general framework of dual approximation operators. Int. J. Approx. Reason. 88: 295-305 (2017) - 2016
- [b1]Francisco Herrera, Sebastián Ventura, Rafael Bello, Chris Cornelis, Amelia Zafra, Dánel Sánchez Tarragó, Sarah Vluymans:
Multiple Instance Learning - Foundations and Algorithms. Springer 2016, ISBN 978-3-319-47758-9, pp. 1-233 - [j54]Nele Verbiest, Joaquín Derrac, Chris Cornelis, Salvador García, Francisco Herrera:
Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis. Appl. Soft Comput. 38: 10-22 (2016) - [j53]Nele Verbiest, Sarah Vluymans, Chris Cornelis, Nicolás García-Pedrajas, Yvan Saeys:
Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets. Appl. Soft Comput. 44: 75-88 (2016) - [j52]Enislay Ramentol, I. Gondres, S. Lajes, Rafael Bello, Yaile Caballero, Chris Cornelis, Francisco Herrera:
Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm. Eng. Appl. Artif. Intell. 48: 134-139 (2016) - [j51]Lynn D'eer, Chris Cornelis, Yiyu Yao:
A semantically sound approach to Pawlak rough sets and covering-based rough sets. Int. J. Approx. Reason. 78: 62-72 (2016) - [j50]Sarah Vluymans, Isaac Triguero, Chris Cornelis, Yvan Saeys:
EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data. Neurocomputing 216: 596-610 (2016) - [j49]Lynn D'eer, Mauricio Restrepo, Chris Cornelis, Jonatan Gómez:
Neighborhood operators for covering-based rough sets. Inf. Sci. 336: 21-44 (2016) - [j48]Sarah Vluymans, Dánel Sánchez Tarragó, Yvan Saeys, Chris Cornelis, Francisco Herrera:
Fuzzy rough classifiers for class imbalanced multi-instance data. Pattern Recognit. 53: 36-45 (2016) - [j47]Sarah Vluymans, Dánel Sánchez Tarragó, Yvan Saeys, Chris Cornelis, Francisco Herrera:
Fuzzy Multi-Instance Classifiers. IEEE Trans. Fuzzy Syst. 24(6): 1395-1409 (2016) - [c56]Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys:
Fuzzy rough sets for self-labelling: An exploratory analysis. FUZZ-IEEE 2016: 931-938 - [c55]Lynn D'eer, Chris Cornelis, Yiyu Yao:
A Semantical Approach to Rough Sets and Dominance-Based Rough Sets. IPMU (2) 2016: 23-35 - 2015
- [j46]Lynn D'eer, Nele Verbiest, Chris Cornelis, Lluís Godo:
A comprehensive study of implicator-conjunctor-based and noise-tolerant fuzzy rough sets: Definitions, properties and robustness analysis. Fuzzy Sets Syst. 275: 1-38 (2015) - [j45]Sarah Vluymans, Lynn D'eer, Yvan Saeys, Chris Cornelis:
Applications of Fuzzy Rough Set Theory in Machine Learning: a Survey. Fundam. Informaticae 142(1-4): 53-86 (2015) - [j44]Enislay Ramentol, Sarah Vluymans, Nele Verbiest, Yaile Caballero, Rafael Bello, Chris Cornelis, Francisco Herrera:
IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Trans. Fuzzy Syst. 23(5): 1622-1637 (2015) - [c54]Isaac Triguero, Mikel Galar, Sarah Vluymans, Chris Cornelis, Humberto Bustince, Francisco Herrera, Yvan Saeys:
Evolutionary undersampling for imbalanced big data classification. CEC 2015: 715-722 - [c53]Lynn D'eer, Chris Cornelis, Daniel Sánchez:
Fuzzy Covering based Rough Sets Revisited. IFSA-EUSFLAT 2015 - [c52]Sarah Vluymans, Yvan Saeys, Chris Cornelis, Ankur Teredesai, Martine De Cock:
Fuzzy Rough Set Prototype Selection for Regression. FUZZ-IEEE 2015: 1-8 - [c51]Sarah Vluymans, Hasan Asfoor, Yvan Saeys, Chris Cornelis, Matthew E. Tolentino, Ankur Teredesai, Martine De Cock:
Distributed fuzzy rough prototype selection for Big Data regression. NAFIPS/WConSC 2015: 1-6 - [c50]Richard Jensen, Sarah Vluymans, Neil Mac Parthaláin, Chris Cornelis, Yvan Saeys:
Semi-Supervised Fuzzy-Rough Feature Selection. RSFDGrC 2015: 185-195 - [c49]Lynn D'eer, Chris Cornelis:
New Neighborhood Based Rough Sets. RSKT 2015: 191-201 - [p5]Masahiro Inuiguchi, Wei-Zhi Wu, Chris Cornelis, Nele Verbiest:
Fuzzy-Rough Hybridization. Handbook of Computational Intelligence 2015: 425-451 - 2014
- [j43]Nele Verbiest, Enislay Ramentol, Chris Cornelis, Francisco Herrera:
Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection. Appl. Soft Comput. 22: 511-517 (2014) - [j42]Chris Cornelis, Jesús Medina, Nele Verbiest:
Multi-adjoint fuzzy rough sets: Definition, properties and attribute selection. Int. J. Approx. Reason. 55(1): 412-426 (2014) - [j41]Mauricio Restrepo, Chris Cornelis, Jonatan Gómez:
Duality, conjugacy and adjointness of approximation operators in covering-based rough sets. Int. J. Approx. Reason. 55(1): 469-485 (2014) - [j40]Mauricio Restrepo, Chris Cornelis, Jonatan Gómez:
Partial order relation for approximation operators in covering based rough sets. Inf. Sci. 284: 44-59 (2014) - [j39]Lala Septem Riza, Andrzej Janusz, Christoph Bergmeir, Chris Cornelis, Francisco Herrera, Dominik Slezak, José Manuel Benítez:
Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "RoughSets". Inf. Sci. 287: 68-89 (2014) - [j38]Dánel Sánchez Tarragó, Chris Cornelis, Rafael Bello, Francisco Herrera:
A multi-instance learning wrapper based on the Rocchio classifier for web index recommendation. Knowl. Based Syst. 59: 173-181 (2014) - [c48]Hasan Asfoor, Rajagopalan Srinivasan, Gayathri Vasudevan, Nele Verbiest, Chris Cornelis, Matthew E. Tolentino, Ankur Teredesai, Martine De Cock:
Computing fuzzy rough approximations in large scale information systems. IEEE BigData 2014: 9-16 - [c47]Richard Jensen, Neil Mac Parthaláin, Chris Cornelis:
Feature grouping-based fuzzy-rough feature selection. FUZZ-IEEE 2014: 1488-1495 - [e4]Chris Cornelis, Marzena Kryszkiewicz, Dominik Slezak, Ernestina Menasalvas Ruiz, Rafael Bello, Lin Shang:
Rough Sets and Current Trends in Computing - 9th International Conference, RSCTC 2014, Granada and Madrid, Spain, July 9-13, 2014. Proceedings. Lecture Notes in Computer Science 8536, Springer 2014, ISBN 978-3-319-08643-9 [contents] - [e3]Marzena Kryszkiewicz, Chris Cornelis, Davide Ciucci, Jesús Medina-Moreno, Hiroshi Motoda, Zbigniew W. Ras:
Rough Sets and Intelligent Systems Paradigms - Second International Conference, RSEISP 2014, Held as Part of JRS 2014, Granada and Madrid, Spain, July 9-13, 2014. Proceedings. Lecture Notes in Computer Science 8537, Springer 2014, ISBN 978-3-319-08728-3 [contents] - 2013
- [j37]Germán Hurtado Martín, Steven Schockaert, Chris Cornelis, Helga Naessens:
Using semi-structured data for assessing research paper similarity. Inf. Sci. 221: 245-261 (2013) - [j36]Nele Verbiest, Chris Cornelis, Francisco Herrera:
FRPS: A Fuzzy Rough Prototype Selection method. Pattern Recognit. 46(10): 2770-2782 (2013) - [j35]Joaquín Derrac, Nele Verbiest, Salvador García, Chris Cornelis, Francisco Herrera:
On the use of evolutionary feature selection for improving fuzzy rough set based prototype selection. Soft Comput. 17(2): 223-238 (2013) - [j34]Patricia Victor, Nele Verbiest, Chris Cornelis, Martine De Cock:
Enhancing the trust-based recommendation process with explicit distrust. ACM Trans. Web 7(2): 6:1-6:19 (2013) - [c46]Chris Cornelis, Martine De Cock, Glad Deschrijver, Mike Nachtegael, Steven Schockaert:
An Excellent Guest Professor at Ghent University. A Tribute to Prof. Dr. Da Ruan 2013: 109-114 - [c45]Nele Verbiest, Chris Cornelis, Richard Jensen:
Quality, frequency and similarity based fuzzy nearest neighbor classification. FUZZ-IEEE 2013: 1-8 - [c44]Lynn D'eer, Nele Verbiest, Chris Cornelis, Lluís Godo:
Implicator-Conjunctor Based Models of Fuzzy Rough Sets: Definitions and Properties. RSFDGrC 2013: 169-179 - [c43]Nele Verbiest, Chris Cornelis, Francisco Herrera:
OWA-FRPS: A Prototype Selection Method Based on Ordered Weighted Average Fuzzy Rough Set Theory. RSFDGrC 2013: 180-190 - [e2]Pawan Lingras, Marcin Wolski, Chris Cornelis, Sushmita Mitra, Piotr Wasilewski:
Rough Sets and Knowledge Technology - 8th International Conference, RSKT 2013, Halifax, NS, Canada, October 11-14, 2013, Proceedings. Lecture Notes in Computer Science 8171, Springer 2013, ISBN 978-3-642-41298-1 [contents] - 2012
- [j33]Nele Verbiest, Chris Cornelis, Patricia Victor, Enrique Herrera-Viedma:
Trust and distrust aggregation enhanced with path length incorporation. Fuzzy Sets Syst. 202: 61-74 (2012) - [j32]Joaquín Derrac, Chris Cornelis, Salvador García, Francisco Herrera:
Enhancing evolutionary instance selection algorithms by means of fuzzy rough set based feature selection. Inf. Sci. 186(1): 73-92 (2012) - [j31]Bart Van Gasse, Chris Cornelis, Glad Deschrijver, Etienne E. Kerre:
The standard completeness of interval-valued monoidal t-norm based logic. Inf. Sci. 189: 63-76 (2012) - [c42]Nele Verbiest, Chris Cornelis, Richard Jensen:
Fuzzy rough positive region based nearest neighbour classification. FUZZ-IEEE 2012: 1-7 - [c41]Nele Verbiest, Enislay Ramentol, Chris Cornelis, Francisco Herrera:
Improving SMOTE with Fuzzy Rough Prototype Selection to Detect Noise in Imbalanced Classification Data. IBERAMIA 2012: 169-178 - [c40]Dieter Mourisse, Els Lefever, Nele Verbiest, Yvan Saeys, Martine De Cock, Chris Cornelis:
SBFC: An Efficient Feature Frequency-Based Approach to Tackle Cross-Lingual Word Sense Disambiguation. TSD 2012: 248-255 - 2011
- [j30]Patricia Victor, Chris Cornelis, Martine De Cock, Ankur Teredesai:
Trust- and Distrust-Based Recommendations for Controversial Reviews. IEEE Intell. Syst. 26(1): 48-55 (2011) - [j29]Patricia Victor, Chris Cornelis, Martine De Cock, Enrique Herrera-Viedma:
Practical aggregation operators for gradual trust and distrust. Fuzzy Sets Syst. 184(1): 126-147 (2011) - [j28]Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, Martine De Cock:
Modelling gene and protein regulatory networks with Answer Set Programming. Int. J. Data Min. Bioinform. 5(2): 209-229 (2011) - [j27]Richard Jensen, Chris Cornelis:
Fuzzy-rough nearest neighbour classification and prediction. Theor. Comput. Sci. 412(42): 5871-5884 (2011) - [j26]Richard Jensen, Chris Cornelis:
Fuzzy-Rough Nearest Neighbour Classification. Trans. Rough Sets 13: 56-72 (2011) - [c39]Joaquín Derrac, Chris Cornelis, Salvador García, Francisco Herrera:
A Preliminary Study on the Use of Fuzzy Rough Set Based Feature Selection for Improving Evolutionary Instance Selection Algorithms. IWANN (1) 2011: 174-182 - [c38]Germán Hurtado Martín, Steven Schockaert, Chris Cornelis, Helga Naessens:
Finding Similar Research Papers using Language Models. SPIM 2011: 106-113 - [p4]Patricia Victor, Martine De Cock, Chris Cornelis:
Trust and Recommendations. Recommender Systems Handbook 2011: 645-675 - [p3]Bart Van Gasse, Chris Cornelis, Glad Deschrijver:
Interval-Valued Algebras and Fuzzy Logics. 35 Years of Fuzzy Set Theory 2011: 57-82 - [e1]Chris Cornelis, Glad Deschrijver, Mike Nachtegael, Steven Schockaert, Yun Shi:
35 Years of Fuzzy Set Theory - Celebratory Volume Dedicated to the Retirement of Etienne E. Kerre. Studies in Fuzziness and Soft Computing 261, Springer 2011, ISBN 978-3-642-16628-0 [contents] - 2010
- [j25]Chris Cornelis, Richard Jensen, Germán Hurtado Martín, Dominik Slezak:
Attribute selection with fuzzy decision reducts. Inf. Sci. 180(2): 209-224 (2010) - [j24]Bart Van Gasse, Glad Deschrijver, Chris Cornelis, Etienne E. Kerre:
Filters of residuated lattices and triangle algebras. Inf. Sci. 180(16): 3006-3020 (2010) - [c37]Timur Fayruzov, Jeroen Janssen, Chris Cornelis, Dirk Vermeir, Martine De Cock:
Extending boolean regulatory network models with answer set programming. BIBM Workshops 2010: 207-212 - [c36]Germán Hurtado Martín, Steven Schockaert, Chris Cornelis, Helga Naessens:
Metadata Impact on Research Paper Similarity. ECDL 2010: 457-460 - [c35]Richard Jensen, Chris Cornelis:
Fuzzy-rough instance selection. FUZZ-IEEE 2010: 1-7 - [c34]Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, Martine De Cock:
Efficient Solving of Time-dependent Answer Set Programs. ICLP (Technical Communications) 2010: 64-73 - [c33]Nele Verbiest, Chris Cornelis, Patricia Victor, Enrique Herrera-Viedma:
Strategies for Incorporating Knowledge Defects and Path Length in Trust Aggregation. IEA/AIE (3) 2010: 450-459 - [c32]