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2020 – today
- 2024
- [e13]Mengjun Hu
, Chris Cornelis
Rough Sets - International Joint Conference, IJCRS 2024, Halifax, NS, Canada, May 17-20, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14839, Springer 2024, ISBN 978-3-031-65664-4 [contents] - [e12]Mengjun Hu
Rough Sets - International Joint Conference, IJCRS 2024, Halifax, NS, Canada, May 17-20, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14840, Springer 2024, ISBN 978-3-031-65667-5 [contents] - [i3]Nikita Neveditsin, Pawan Lingras, Vijay Mago:
Clinical Insights: A Comprehensive Review of Language Models in Medicine. CoRR abs/2408.11735 (2024) - 2023
- [c86]Gaurav Rao, David W. Savage, Vijay Mago, Pawan Lingras:
A Survey on Technologies Used During out of Hospital Cardiac Arrest. HEALTHINF 2023: 477-488 - [e11]Morusupalli Raghava
Multi-disciplinary Trends in Artificial Intelligence - 16th International Conference, MIWAI 2023, Hyderabad, India, July 21-22, 2023, Proceedings. Lecture Notes in Computer Science 14078, Springer 2023, ISBN 978-3-031-36401-3 [contents] - [e10]Scott Dick, Vladik Kreinovich, Pawan Lingras:
Applications of Fuzzy Techniques - Proceedings of the 2022 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2022, Halifax, NS, Canada, 31 May - 3 June 2022. Lecture Notes in Networks and Systems 500, Springer 2023, ISBN 978-3-031-16037-0 [contents] - 2022
- [j43]Gaurav Rao
AEDNav: indoor navigation for locating automated external defibrillator. BMC Medical Informatics Decis. Mak. 22-S(2): 159 (2022) - 2020
- [j42]Gaurav Rao, Salimur Choudhury, Pawan Lingras, David W. Savage, Vijay Mago
SURF: identifying and allocating resources during Out-of-Hospital Cardiac Arrest. BMC Medical Informatics Decis. Mak. 20-S(11): 313 (2020) - [c85]Nikita Neveditsin, Ross MacDonald, Pawan Lingras, Trent Hillard:
Modeling User Feedback: Fuzzy sampling, Portability, and Degree of Annoyance. FUZZ-IEEE 2020: 1-7
2010 – 2019
- 2019
- [j41]Hong Yu, Yun Chen, Pawan Lingras, Guoyin Wang:
A three-way cluster ensemble approach for large-scale data. Int. J. Approx. Reason. 115: 32-49 (2019) - [c84]Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Zheng Qin, Trent Hillard:
Sampling Using Fuzzy and Crisp Clustering to Improve Recall of Building Comfort Feedback. FUZZ-IEEE 2019: 1-6 - [c83]Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Trent Hillard:
Effect of Maximizing Recall and Agglomeration of Feedback on Accuracy. IFSA/NAFIPS 2019: 351-361 - 2018
- [c82]Matthew Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras:
Fuzzy Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. IEA/AIE 2018: 661-669 - 2017
- [c81]Matthew Triff, Glavin Wiechert, Pawan Lingras:
Nonlinear classification, linear clustering, evolutionary semi-supervised three-way decisions: A comparison. FUZZ-IEEE 2017: 1-6 - [c80]Matthew Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras:
Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. ISMIS 2017: 530-539 - 2016
- [j40]Pawan Lingras:
Book Review: Cognitive Computing: Theory and Applications. IEEE Intell. Informatics Bull. 17(1): 27 (2016) - [j39]Asma Ammar, Zied Elouedi
Meta-clustering of possibilistically segmented retail datasets. Fuzzy Sets Syst. 286: 173-196 (2016) - [c79]Glavin Wiechert, Matthew Triff, Zhixing Liu, Zhicheng Yin, Shuai Zhao, Ziyun Zhong, Runxing Zhaou, Pawan Lingras:
Identifying users and activities with cognitive signal processing from a wearable headband. ICCI*CC 2016: 129-136 - [c78]Glavin Wiechert, Matthew Triff, Zhixing Liu, Zhicheng Yin, Shuai Zhao, Ziyun Zhong, Pawan Lingras:
Evolutionary semi-supervised rough categorization of brain signals from a wearable headband. CEC 2016: 3131-3138 - [c77]Pawan Lingras, Matthew Triff:
Advances in Rough and Soft Clustering: Meta-Clustering, Dynamic Clustering, Data-Stream Clustering. IJCRS 2016: 3-22 - 2015
- [j38]Pawan Lingras, Sugata Sanyal:
Book Review: Big Data Analytics. IEEE Intell. Informatics Bull. 16(1): 28-29 (2015) - [j37]Pawan Lingras, Farhana Haider:
Partially ordered rough ensemble clustering for multigranular representations. Intell. Data Anal. 19(s1): S103-S116 (2015) - [j36]Asma Ammar, Zied Elouedi, Pawan Lingras:
Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories. Int. J. Intell. Syst. 30(6): 676-706 (2015) - [j35]Pawan Lingras
Fuzzy and Crisp Recursive Profiling of Online Reviewers and Businesses. IEEE Trans. Fuzzy Syst. 23(4): 1242-1258 (2015) - [c76]Jason P. Rhinelander
Visual Predictions of Traffic Conditions. Canadian AI 2015: 122-129 - [c75]Pawan Lingras, Farhana Haider:
Combining Rough Clustering Schemes as a Rough Ensemble. RSKT 2015: 383-394 - 2014
- [j34]Pawan Lingras, Min Chen, Duoqian Miao:
Qualitative and quantitative combinations of crisp and rough clustering schemes using dominance relations. Int. J. Approx. Reason. 55(1): 238-258 (2014) - [j33]Pawan Lingras, Ahmed Elagamy, Asma Ammar, Zied Elouedi:
Iterative meta-clustering through granular hierarchy of supermarket customers and products. Inf. Sci. 257: 14-31 (2014) - [c74]Asma Ammar, Zied Elouedi, Pawan Lingras:
Rough possibilistic meta-clustering of retail datasets. DSAA 2014: 177-183 - [c73]Asma Ammar, Zied Elouedi, Pawan Lingras:
Decremental Rough Possibilistic K-Modes. ICAIS 2014: 50-59 - [c72]Georg Peters, Pawan Lingras:
Analysis of User-Weighted π Rough k-Means. RSKT 2014: 547-556 - [c71]Asma Ammar, Zied Elouedi, Pawan Lingras:
Semantically Enhanced Clustering in Retail Using Possibilistic K-Modes. RSKT 2014: 753-764 - 2013
- [j32]Georg Peters, Fernando A. Crespo
Soft clustering - Fuzzy and rough approaches and their extensions and derivatives. Int. J. Approx. Reason. 54(2): 307-322 (2013) - [c70]Saurabh Nagrecha, Pawan Lingras, Nitesh V. Chawla
Comparison of Gene Co-expression Networks and Bayesian Networks. ACIIDS (1) 2013: 507-516 - [c69]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Exhaustive Search with Belief Discernibility Matrix and Function. Canadian AI 2013: 162-173 - [c68]Asma Ammar, Zied Elouedi, Pawan Lingras:
The K-Modes Method under Possibilistic Framework. Canadian AI 2013: 211-217 - [c67]Kishore Rathinavel, Pawan Lingras:
A granular recursive fuzzy meta-clustering algorithm for social networks. IFSA/NAFIPS 2013: 567-572 - [c66]Asma Ammar, Zied Elouedi, Pawan Lingras:
The k-modes method using possibility and rough set theories. IFSA/NAFIPS 2013: 1297-1302 - [c65]Asma Ammar, Zied Elouedi, Pawan Lingras:
Incremental Rough Possibilistic K-Modes. MIWAI 2013: 13-24 - [c64]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Discernibility Matrix and Function for Incremental or Large Data. RSFDGrC 2013: 67-76 - [c63]Manish R. Joshi
Enhancing Rough Clustering with Outlier Detection Based on Evidential Clustering. RSFDGrC 2013: 127-137 - [c62]Asma Ammar, Zied Elouedi, Pawan Lingras:
Incremental Possibilistic K-Modes. RSFDGrC 2013: 293-303 - [c61]Matthew Triff, Pawan Lingras:
Recursive Profiles of Businesses and Reviewers on Yelp.com. RSFDGrC 2013: 325-336 - [c60]Asma Ammar, Zied Elouedi, Pawan Lingras:
Decremental Possibilistic K-Modes. SCAI 2013: 15-24 - [p3]Pawan Lingras, Parag Bhalchandra
Rough Support Vectors: Classification, Regression, Clustering. Rough Sets and Intelligent Systems (1) 2013: 491-515 - [e9]Sheela Ramanna, Pawan Lingras, Chattrakul Sombattheera, Aneesh Krishna
Multi-disciplinary Trends in Artificial Intelligence - 7th International Workshop, MIWAI 2013, Krabi, Thailand, December 9-11, 2013. Proceedings. Lecture Notes in Computer Science 8271, Springer 2013, ISBN 978-3-642-44948-2 [contents] - [e8]Pawan Lingras, Marcin Wolski
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] - [i2]S. K. Michael Wong, Y. Y. Yao, Pawan Lingras:
Compatibility of Quantitative and Qualitative Representations of Belief. CoRR abs/1303.5758 (2013) - [i1]S. K. Michael Wong, Pawan Lingras:
Combination of Evidence Using the Principle of Minimum Information Gain. CoRR abs/1304.1135 (2013) - 2012
- [j31]Manish R. Joshi
Correlating Fuzzy and Rough Clustering. Fundam. Informaticae 115(2-3): 233-246 (2012) - [c59]Pawan Lingras, Parag Bhalchandra
Propagation of knowledge from crisp and soft clustering through a granular hierarchy. HIS 2012: 6-11 - [c58]Asma Ammar, Zied Elouedi, Pawan Lingras:
K-Modes Clustering Using Possibilistic Membership. IPMU (3) 2012: 596-605 - [c57]Pawan Lingras, Kishore Rathinavel:
Recursive meta-clustering in a granular network. ISDA 2012: 770-775 - [c56]Asma Ammar, Zied Elouedi, Pawan Lingras:
RPKM: The Rough Possibilistic K-Modes. ISMIS 2012: 81-86 - [c55]Manish R. Joshi
Evidential Clustering or Rough Clustering: The Choice Is Yours. RSKT 2012: 123-128 - [c54]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Heuristic for Attribute Selection Using Belief Discernibility Matrix. RSKT 2012: 129-138 - 2011
- [j30]Cory J. Butz, Ken Konkel, Pawan Lingras:
Join tree propagation utilizing both arc reversal and variable elimination. Int. J. Approx. Reason. 52(7): 948-959 (2011) - [j29]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Classification systems based on rough sets under the belief function framework. Int. J. Approx. Reason. 52(9): 1409-1432 (2011) - [j28]Tianrui Li
Computational Intelligence in Decision Making. Int. J. Comput. Intell. Syst. 4(1) (2011) - [j27]Pawan Lingras, Manish R. Joshi
Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering. Int. J. Comput. Intell. Syst. 4(1): 12-28 (2011) - [j26]Peng Zhang, Manish R. Joshi
Use of Stability and Seasonality Analysis for Optimal Inventory Prediction Models. J. Intell. Syst. 20(2): 147-166 (2011) - [j25]Pawan Lingras, Cory J. Butz:
Conservative and aggressive rough SVR modeling. Theor. Comput. Sci. 412(42): 5885-5901 (2011) - [j24]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Classification with Dynamic Reducts and Belief Functions. Trans. Rough Sets 14: 202-233 (2011) - [j23]Pawan Lingras, Georg Peters:
Rough clustering. WIREs Data Mining Knowl. Discov. 1(1): 64-72 (2011) - [c53]Pawan Lingras, Sarjerao Nimse, N. Darkunde, A. Muley:
Soft clustering from crisp clustering using granulation for mobile call mining. GrC 2011: 410-416 - [c52]Peng Zhang, Manish R. Joshi, Pawan Lingras:
Clustering of Products to Identify Optimal Inventory Prediction Models. IICAI 2011: 451-464 - [c51]Pawan Lingras, Parag Bhalchandra
Crisp and Soft Clustering of Mobile Calls. MIWAI 2011: 147-158 - [c50]Sarjerao Nimse, Pawan Lingras:
History of Set Theory and Its Extensions in the Context of Soft Computing. RSKT 2011: 25 - [c49]Pawan Lingras, Parag Bhalchandra
Comparing Clustering Schemes at Two Levels of Granularity for Mobile Call Mining. RSKT 2011: 696-705 - [e7]Cory J. Butz, Pawan Lingras:
Advances in Artificial Intelligence - 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John's, Canada, May 25-27, 2011. Proceedings. Lecture Notes in Computer Science 6657, Springer 2011, ISBN 978-3-642-21042-6 [contents] - [e6]Bhanu Prasad, Pawan Lingras, Ramakant Nevatia:
Proceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011, Tumkur, Karnataka State, India, December 14-16, 2011. IICAI 2011, ISBN 978-0-9727412-8-6 [contents] - 2010
- [j22]Pawan Lingras, Cory J. Butz:
Rough support vector regression. Eur. J. Oper. Res. 206(2): 445-455 (2010) - [c48]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Rule Discovery Process Based on Rough Sets under the Belief Function Framework. IPMU 2010: 726-736 - [c47]Manish R. Joshi
Rough, fuzzy, interval clustering for web usage mining. ISDA 2010: 397-402 - [c46]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Rough Set Classification for web mining based on dynamic core. ISDA 2010: 403-408 - [c45]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
A Comparison of Dynamic and Static Belief Rough Set Classifier. RSCTC 2010: 366-375 - [c44]Manish R. Joshi
Analysis of Rough and Fuzzy Clustering. RSKT 2010: 679-686 - [p2]Cory J. Butz, Wen Yan, Pawan Lingras, Y. Y. Yao:
The CPT Structure of Variable Elimination in Discrete Bayesian Networks. Advances in Intelligent Information Systems 2010: 245-257 - [e5]Aijun An, Pawan Lingras, Sheila Petty, Runhe Huang:
Active Media Technology, 6th International Conference, AMT 2010, Toronto, Canada, August 28-30, 2010. Proceedings. Lecture Notes in Computer Science 6335, Springer 2010, ISBN 978-3-642-15469-0 [contents] - [e4]Jian Yu, Salvatore Greco
Rough Set and Knowledge Technology - 5th International Conference, RSKT 2010, Beijing, China, October 15-17, 2010. Proceedings. Lecture Notes in Computer Science 6401, Springer 2010, ISBN 978-3-642-16247-3 [contents] - [e3]James F. Peters, Andrzej Skowron, Roman Slowinski, Pawan Lingras, Duoqian Miao, Shusaku Tsumoto:
Transactions on Rough Sets XII. Lecture Notes in Computer Science 6190, Springer 2010, ISBN 978-3-642-14466-0 [contents]
2000 – 2009
- 2009
- [j21]Pawan Lingras, Min Chen, Duoqian Miao:
Semi-supervised Rough Cost/Benefit Decisions. Fundam. Informaticae 94(2): 233-244 (2009) - [j20]Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras:
A formal comparison of variable elimination and arc reversal in Bayesian network inference. Intell. Decis. Technol. 3(3): 173-180 (2009) - [j19]Pawan Lingras, Min Chen, Duoqian Miao:
Rough Cluster Quality Index Based on Decision Theory. IEEE Trans. Knowl. Data Eng. 21(7): 1014-1026 (2009) - [c43]Pawan Lingras:
Rough K-medoids clustering using GAs. IEEE ICCI 2009: 315-319 - [c42]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Belief Rough Set Classifier. Canadian AI 2009: 257-261 - [c41]Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras:
A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference. FLAIRS 2009 - [c40]Cory J. Butz, Ken Konkel, Pawan Lingras:
Join Tree Propagation Utilizing Both Arc Reversal and Variable Elimination. FLAIRS 2009 - [c39]Manish R. Joshi, Virendrakumar C. Bhavsar, Pawan Lingras:
An Algorithm for the Estimation of a Time Period of 2-Sequences. IICAI 2009: 71-88 - [c38]Manish R. Joshi
Evolutionary and Iterative Crisp and Rough Clustering I: Theory. PReMI 2009: 615-620 - [c37]Manish R. Joshi
Evolutionary and Iterative Crisp and Rough Clustering II: Experiments. PReMI 2009: 621-627 - [c36]Manish R. Joshi
Rough Set Year in India 2009. RSFDGrC 2009: 67-68 - [c35]Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
Dynamic Reduct from Partially Uncertain Data Using Rough Sets. RSFDGrC 2009: 160-167 - [c34]Yiyu Yao, Pawan Lingras, Ruizhi Wang, Duoqian Miao:
Interval Set Cluster Analysis: A Re-formulation. RSFDGrC 2009: 398-405 - [c33]Pawan Lingras:
Evolutionary Rough K-Means Clustering. RSKT 2009: 68-75 - [e2]Bhanu Prasad, Pawan Lingras, Ashwin Ram:
Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009, Tumkur, Karnataka, India, December 16-18, 2009. IICAI 2009, ISBN 978-0-9727412-7-9 [contents] - 2008
- [b1]Rajendra Akerkar, Pawan Lingras:
Building an intelligent web - theory and practice: contains IBM DB2 Express-C9. Jones and Bartlett Publishers 2008, ISBN 978-0-7637-4137-2, pp. I-XI, 1-326 - [c32]Cory J. Butz, Pawan Lingras, Ken Konkel:
A Web-Based Interface for Hiding Bayesian Network Inference. ISMIS 2008: 612-617 - [c31]Pawan Lingras, Min Chen, Duoqian Miao:
Precision of Rough Set Clustering. RSCTC 2008: 369-378 - [c30]Pawan Lingras, Min Chen, Duoqian Miao:
Rough Multi-category Decision Theoretic Framework. RSKT 2008: 676-683 - [p1]Pawan Lingras, Ming Zhong, Satish Sharma:
Evolutionary Regression and Neural Imputations of Missing Values. Soft Computing Applications in Industry 2008: 151-163 - 2007
- [j18]Pawan Lingras, Cory J. Butz:
Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification. Inf. Sci. 177(18): 3782-3798 (2007) - [j17]Pawan Lingras:
Applications of Rough Set Based K-Means, Kohonen SOM, GA Clustering. Trans. Rough Sets 7: 120-139 (2007) - [c29]Pawan Lingras, Richard Jensen
Survey of Rough and Fuzzy Hybridization. FUZZ-IEEE 2007: 1-6 - [c28]Pawan Lingras, Rucha Lingras:
Adaptive hyperlinks Using Page Access Sequences and Minimum Spanning Trees. FUZZ-IEEE 2007: 1-6 - [c27]Pawan Lingras, Cory J. Butz:
Precision and Recall in Rough Support Vector Machines. GrC 2007: 654-658 - [c26]Keith Bain, Jason Hines, Pawan Lingras, Yumei Qin:
Using Speech Recognition and Intelligent Search Tools to Enhance Information Accessibility. HCI (7) 2007: 214-223 - [e1]Jingtao Yao, Pawan Lingras, Wei-Zhi Wu, Marcin S. Szczuka, Nick Cercone, Dominik Slezak:
Rough Sets and Knowledge Technology, Second International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007, Proceedings. Lecture Notes in Computer Science 4481, Springer 2007, ISBN 978-3-540-72457-5 [contents] - 2006
- [c25]Ravipriya Ranatunga, Sisil Kumarawadu, Pawan Lingras, Tsu-Tian Lee:
A New Paradigm for Intelligent Collision Avoidance via Interactive and Interdependent Generic Maneuvers. SMC 2006: 4625-4630 - 2005
- [j16]Pawan Lingras, Xiandong Huang:
Statistical, Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based Approaches. Artif. Intell. Rev. 23(1): 3-29 (2005) - [j15]Chad West, Stephanie MacDonald, Pawan Lingras, Greg Adams:
Relationship between Product Based Loyalty and Clustering based on Supermarket Visit and Spending Patterns. Int. J. Comput. Sci. Appl. 2(2): 85-100 (2005) - [j14]Pawan Lingras, Mofreh Hogo
Temporal analysis of clusters of supermarket customers: conventional versus interval set approach. Inf. Sci. 172(1-2): 215-240 (2005) - [c24]Pawan Lingras, Cory J. Butz:
Interval set representations of 1-v-r support vector machine multi-classifiers. GrC 2005: 193-198 - [c23]Cory J. Butz, Pawan Lingras:
On the Practical Irrelevance of Diverging Implication between Probabilistic Conditional Independence and Embedded Multivalued Dependency. IICAI 2005: 2464-2475 - [c22]Pawan Lingras, Cory J. Butz:
Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiers. RSFDGrC (2) 2005: 166-173 - 2004
- [j13]Mofreh Hogo, Miroslav Snorek, Pawan Lingras:
Temporal Versus Latest Snapshot Web Usage Mining Using Kohonen Som And Modified Kohonen Som Based on The Properties of Rough Sets Theory. Int. J. Artif. Intell. Tools 13(3): 569-592 (2004) - [j12]Pawan Lingras, Chad West:
Interval Set Clustering of Web Users with Rough K-Means. J. Intell. Inf. Syst. 23(1): 5-16 (2004) - [j11]Pawan Lingras, Mofreh Hogo, Miroslav Snorek:
Interval set clustering of web users using modified Kohonen self-organizing maps based on the properties of rough sets. Web Intell. Agent Syst. 2(3): 217-225 (2004) - [c21]Ming Zhong, Satish Sharma, Pawan Lingras:
Analyzing the Performance of Genetically Designed Short-Term Traffic Prediction Models Based on Road Types and Functional Classes. IEA/AIE 2004: 1133-1145 - [c20]Pawan Lingras, Mofreh Hogo, Miroslav Snorek:
Temporal Cluster Migration Matrices for Web Usage Mining. Web Intelligence 2004: 441-444 - [c19]Yiyu Yao, Jingtao Yao, Cory J. Butz, Pawan Lingras, Dawn N. Jutla:
Web-based Support Systems (WSS): A Report of the WIC Canada Research Centre. Web Intelligence 2004: 787-788 - 2003
- [j10]Cedric Davies, Pawan Lingras:
Genetic algorithms for rerouting shortest paths in dynamic and stochastic networks. Eur. J. Oper. Res. 144(1): 27-38 (2003) - [c18]Pawan Lingras, Rui Yan, Chad West:
Fuzzy C-Means Clustering of Web Users for Educational Sites. AI 2003: 557-562 - [c17]Mofreh Hogo, Pawan Lingras, Miroslav Snorek:
Conventional Versus Interval Clustering Using Kohonen Networks. ICEIS (2) 2003: 250-257 - [c16]Pawan Lingras, Rui Yan, Adish Jain:
Clustering of Web Users: K-Means vs. Fuzzy C-Means. IICAI 2003: 1062-1073 - [c15]Pawan Lingras, Rui Yan, Mofreh Hogo:
Rough Set Based Clustering: Evolutionary, Neural, and Statistical Approaches. IICAI 2003: 1074-1087 - [c14]Chad West, Adish Jain, Pawan Lingras, Bill Leonard:
Supermarket Customer Attrition Analysis Based on Cluster Membership Patterns. IICAI 2003: 1132-1140 - [c13]Pawan Lingras, Mofreh Hogo
Clustering Supermarket Customers Using Rough Set Based Kohonen Networks. ISMIS 2003: 169-173 - [c12]Pawan Lingras, Rui Yan, Chad West:
Comparison of Conventional and Rough K-Means Clustering. RSFDGrC 2003: 130-137 - [c11]Mofreh Hogo, Miroslav Snorek, Pawan Lingras:
Temporal Web Usage Mining. Web Intelligence 2003: 450-453 - 2002
- [c10]Pawan Lingras:
Rough set clustering for Web mining. FUZZ-IEEE 2002: 1039-1044 - [c9]Pawan Lingras, Y. Y. Yao:
Time Complexity of Rough Clustering: GAs versus K-Means. Rough Sets and Current Trends in Computing 2002: 263-270 - 2001
- [j9]Pawan Lingras, Cedric Davies:
Application of Rough Genetic Algorithms. Comput. Intell. 17(3): 435-445 (2001) - [j8]Pawan Lingras:
Fuzzy-rough and rough-fuzzy serial combinations in neurocomputing. Neurocomputing 36(1-4): 29-44 (2001) - [j7]Pawan Lingras:
Unsupervised Rough Set Classification Using GAs. J. Intell. Inf. Syst. 16(3): 215-228 (2001) - [c8]Pawan Lingras, Paul Mountford:
Time Delay Neural Networks Designed Using Genetic Algorithms for Short Term Inter-City Traffic Forecasting. IEA/AIE 2001: 290-299
1990 – 1999
- 1999
- [c7]Pawan Lingras, Cedric Davies:
Rough Genetic Algorithms. RSFDGrC 1999: 38-46 - 1998
- [j6]Y. Y. Yao
Interpretation of Belief Functions in The Theory of Rough Sets. Inf. Sci. 104(1-2): 81-106 (1998) - [j5]Pawan Lingras:
Comparison of Neofuzzy and Rough Neural Networks. Inf. Sci. 110(3-4): 207-215 (1998) - [j4]Pawan Lingras, Y. Y. Yao:
Data Mining Using Extensions of the Rough Set Model. J. Am. Soc. Inf. Sci. 49(5): 415-422 (1998) - 1996
- [j3]Pawan Lingras:
Evidential Comparisons Using Belief Functions, Rough Sets and Nonmonotonic Preferences. Intell. Autom. Soft Comput. 2(2): 203-209 (1996) - 1994
- [j2]S. K. Michael Wong, Pawan Lingras:
Representation of Qualitative User Preference by Quantitative Belief Functions. IEEE Trans. Knowl. Data Eng. 6(1): 72-78 (1994) - 1993
- [c6]Pawan Lingras:
Combination of Evidence in Rough Set Theory. ICCI 1993: 289-293 - [c5]C. W. R. Chau, Pawan Lingras, S. K. Michael Wong:
Upper and Lower Entropies of Belief Functions Using Compatible Probability Functions. ISMIS 1993: 306-315 - 1991
- [c4]S. K. Michael Wong, Pawan Lingras, Yiyu Yao:
Propagation of Preference Relations in Qualitative Inference Networks. IJCAI 1991: 1204-1209 - [c3]S. K. Michael Wong, Pawan Lingras, Yiyu Yao:
Towards Implementing Valuation Based Systems with Relational Databases. ISMIS 1991: 172-182 - [c2]S. K. Michael Wong, Yiyu Yao, Pawan Lingras:
Compatibility of Quantitative and Qualitative Representations of Belief. UAI 1991: 418-424 - 1990
- [j1]Pawan Lingras, S. K. Michael Wong:
Two Perspectives of the Dempster-Shafer Theory of Belief Functions. Int. J. Man Mach. Stud. 33(4): 467-487 (1990)
1980 – 1989
- 1988
- [c1]Pawan Lingras, S. K. Michael Wong:
An Optimistic Rule for Accumulation of Evidence. ISMIS 1988: 60-69
Coauthor Index
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last updated on 2024-11-11 21:28 CET by the dblp team
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