Pawan Lingras

ORCID

Publication Activity (10 Years)

Years Active: 1988-2023
Publications (10 Years): 15

Top Venues

RSFDGrC

IFSA/NAFIPS

Int. J. Approx. Reason.

RSKT

Publications

Gaurav Rao, David W. Savage, Vijay Mago, Pawan Lingras
A Survey on Technologies Used During out of Hospital Cardiac Arrest. HEALTHINF (2023)
Gaurav Rao, Vijay Mago, Pawan Lingras, David W. Savage
AEDNav: indoor navigation for locating automated external defibrillator. BMC Medical Informatics Decis. Mak. (2) (2022)
Nikita Neveditsin, Ross MacDonald, Pawan Lingras, Trent Hillard
Modeling User Feedback: Fuzzy sampling, Portability, and Degree of Annoyance. FUZZ-IEEE (2020)
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. (11) (2020)
Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Trent Hillard
Effect of Maximizing Recall and Agglomeration of Feedback on Accuracy. IFSA/NAFIPS (2019)
Hong Yu, Yun Chen, Pawan Lingras, Guoyin Wang
A three-way cluster ensemble approach for large-scale data. Int. J. Approx. Reason. 115 (2019)
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)
Matt 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)
Matt Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras
Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. ISMIS (2017)
Matt Triff, Glavin Wiechert, Pawan Lingras
Nonlinear classification, linear clustering, evolutionary semi-supervised three-way decisions: A comparison. FUZZ-IEEE (2017)
Pawan Lingras
Book Review: Cognitive Computing: Theory and Applications. IEEE Intell. Informatics Bull. 17 (1) (2016)
Pawan Lingras, Matt Triff
Advances in Rough and Soft Clustering: Meta-Clustering, Dynamic Clustering, Data-Stream Clustering. IJCRS (2016)
Glavin Wiechert, Matt 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)
Asma Ammar, Zied Elouedi, Pawan Lingras
Meta-clustering of possibilistically segmented retail datasets. Fuzzy Sets Syst. 286 (2016)
Glavin Wiechert, Matt 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)
Pawan Lingras, Farhana Haider
Partially ordered rough ensemble clustering for multigranular representations. Intell. Data Anal. 19 (s1) (2015)
Jason P. Rhinelander, Mathew Kallada, Pawan Lingras
Visual Predictions of Traffic Conditions. Canadian Conference on AI (2015)
Asma Ammar, Zied Elouedi, Pawan Lingras
Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories. Int. J. Intell. Syst. 30 (6) (2015)
Pawan Lingras, Sugata Sanyal
Book Review: Big Data Analytics. IEEE Intell. Informatics Bull. 16 (1) (2015)
Pawan Lingras, Farhana Haider
Combining Rough Clustering Schemes as a Rough Ensemble. RSKT (2015)
Pawan Lingras, Matt Triff
Fuzzy and Crisp Recursive Profiling of Online Reviewers and Businesses. IEEE Trans. Fuzzy Syst. 23 (4) (2015)
Asma Ammar, Zied Elouedi, Pawan Lingras
Decremental Rough Possibilistic K-Modes. ICAIS (2014)
Asma Ammar, Zied Elouedi, Pawan Lingras
Rough possibilistic meta-clustering of retail datasets. DSAA (2014)
Asma Ammar, Zied Elouedi, Pawan Lingras
Semantically Enhanced Clustering in Retail Using Possibilistic K-Modes. RSKT (2014)
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) (2014)
Pawan Lingras, Ahmed Elagamy, Asma Ammar, Zied Elouedi
Iterative meta-clustering through granular hierarchy of supermarket customers and products. Inf. Sci. 257 (2014)
Georg Peters, Pawan Lingras
Analysis of User-Weighted π Rough k-Means. RSKT (2014)
Asma Ammar, Zied Elouedi, Pawan Lingras
The K-Modes Method under Possibilistic Framework. Canadian Conference on AI (2013)
Kishore Rathinavel, Pawan Lingras
A granular recursive fuzzy meta-clustering algorithm for social networks. IFSA/NAFIPS (2013)
Asma Ammar, Zied Elouedi, Pawan Lingras
Incremental Rough Possibilistic K-Modes. MIWAI (2013)
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) (2013)
Matt Triff, Pawan Lingras
Recursive Profiles of Businesses and Reviewers on Yelp.com. RSFDGrC (2013)
Manish Joshi, Pawan Lingras
Enhancing Rough Clustering with Outlier Detection Based on Evidential Clustering. RSFDGrC (2013)
Asma Ammar, Zied Elouedi, Pawan Lingras
Decremental Possibilistic K-Modes. SCAI (2013)
Asma Ammar, Zied Elouedi, Pawan Lingras
Incremental Possibilistic K-Modes. RSFDGrC (2013)
Saurabh Nagrecha, Pawan Lingras, Nitesh V. Chawla
Comparison of Gene Co-expression Networks and Bayesian Networks. ACIIDS (1) (2013)
S. K. Michael Wong, Y. Y. Yao, Pawan Lingras
Compatibility of Quantitative and Qualitative Representations of Belief CoRR (2013)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Belief Discernibility Matrix and Function for Incremental or Large Data. RSFDGrC (2013)
S. K. Michael Wong, Pawan Lingras
Combination of Evidence Using the Principle of Minimum Information Gain CoRR (2013)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Exhaustive Search with Belief Discernibility Matrix and Function. Canadian Conference on AI (2013)
Asma Ammar, Zied Elouedi, Pawan Lingras
The k-modes method using possibility and rough set theories. IFSA/NAFIPS (2013)
Pawan Lingras, Parag Bhalchandra, Santosh Khamitkar, Satish Mekewad, Ravindra Rathod
Propagation of knowledge from crisp and soft clustering through a granular hierarchy. HIS (2012)
Asma Ammar, Zied Elouedi, Pawan Lingras
RPKM: The Rough Possibilistic K-Modes. ISMIS (2012)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Heuristic for Attribute Selection Using Belief Discernibility Matrix. RSKT (2012)
Pawan Lingras, Kishore Rathinavel
Recursive meta-clustering in a granular network. ISDA (2012)
Manish Joshi, Pawan Lingras, C. Raghavendra Rao
Correlating Fuzzy and Rough Clustering. Fundam. Informaticae 115 (2-3) (2012)
Asma Ammar, Zied Elouedi, Pawan Lingras
K-Modes Clustering Using Possibilistic Membership. IPMU (3) (2012)
Manish Joshi, Pawan Lingras
Evidential Clustering or Rough Clustering: The Choice Is Yours. RSKT (2012)
Peng Zhang, Manish Joshi, Pawan Lingras
Clustering of Products to Identify Optimal Inventory Prediction Models. IICAI (2011)
Pawan Lingras, Parag Bhalchandra, Santosh Khamitkar, Satish Mekewad, Ravindra Rathod
Crisp and Soft Clustering of Mobile Calls. MIWAI (2011)
Pawan Lingras, Manish Joshi
Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering. Int. J. Comput. Intell. Syst. 4 (1) (2011)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Classification with Dynamic Reducts and Belief Functions. Trans. Rough Sets 14 (2011)
Sarjerao Nimse, Pawan Lingras
History of Set Theory and Its Extensions in the Context of Soft Computing. RSKT (2011)
Peng Zhang, Manish Joshi, Pawan Lingras
Use of Stability and Seasonality Analysis for Optimal Inventory Prediction Models. J. Intell. Syst. 20 (2) (2011)
Tianrui Li, Pawan Lingras, Yuefeng Li, Joseph P. Herbert
Computational Intelligence in Decision Making. Int. J. Comput. Intell. Syst. 4 (1) (2011)
Pawan Lingras, Sarjerao Nimse, N. Darkunde, A. Muley
Soft clustering from crisp clustering using granulation for mobile call mining. GrC (2011)
Cory J. Butz, Ken Konkel, Pawan Lingras
Join tree propagation utilizing both arc reversal and variable elimination. Int. J. Approx. Reason. 52 (7) (2011)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Classification systems based on rough sets under the belief function framework. Int. J. Approx. Reason. 52 (9) (2011)
Pawan Lingras, Georg Peters
Rough clustering. WIREs Data Mining Knowl. Discov. 1 (1) (2011)
Pawan Lingras, Parag Bhalchandra, Satish Mekewad, Ravindra Rathod, Santosh Khamitkar
Comparing Clustering Schemes at Two Levels of Granularity for Mobile Call Mining. RSKT (2011)
Pawan Lingras, Cory J. Butz
Conservative and aggressive rough SVR modeling. Theor. Comput. Sci. 412 (42) (2011)
Manish Joshi, Pawan Lingras, Yiyu Yao, Virendrakumar C. Bhavsar
Rough, fuzzy, interval clustering for web usage mining. ISDA (2010)
Manish Joshi, Pawan Lingras, C. Raghavendra Rao
Analysis of Rough and Fuzzy Clustering. RSKT (2010)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Rule Discovery Process Based on Rough Sets under the Belief Function Framework. IPMU (2010)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
A Comparison of Dynamic and Static Belief Rough Set Classifier. RSCTC (2010)
Pawan Lingras, Cory J. Butz
Rough support vector regression. Eur. J. Oper. Res. 206 (2) (2010)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Belief Rough Set Classification for web mining based on dynamic core. ISDA (2010)
Pawan Lingras
Evolutionary Rough K-Means Clustering. RSKT (2009)
Cory J. Butz, Ken Konkel, Pawan Lingras
Join Tree Propagation Utilizing Both Arc Reversal and Variable Elimination. FLAIRS Conference (2009)
Yiyu Yao, Pawan Lingras, Ruizhi Wang, Duoqian Miao
Interval Set Cluster Analysis: A Re-formulation. RSFDGrC (2009)
Manish Joshi, Pawan Lingras
Evolutionary and Iterative Crisp and Rough Clustering II: Experiments. PReMI (2009)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Dynamic Reduct from Partially Uncertain Data Using Rough Sets. RSFDGrC (2009)
Pawan Lingras, Min Chen, Duoqian Miao
Semi-supervised Rough Cost/Benefit Decisions. Fundam. Informaticae 94 (2) (2009)
Pawan Lingras
Rough K-medoids clustering using GAs. IEEE ICCI (2009)
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) (2009)
Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras
A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference. FLAIRS Conference (2009)
Manish Joshi, Virendrakumar C. Bhavsar, Pawan Lingras
An Algorithm for the Estimation of a Time Period of 2-Sequences. IICAI (2009)
Pawan Lingras, Min Chen, Duoqian Miao
Rough Cluster Quality Index Based on Decision Theory. IEEE Trans. Knowl. Data Eng. 21 (7) (2009)
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras
Belief Rough Set Classifier. Canadian Conference on AI (2009)
Manish Joshi, Rabi Nanda Bhaumik, Pawan Lingras, Nitin Patil, Ambuja Salgaonkar, Dominik Slezak
Rough Set Year in India 2009. RSFDGrC (2009)
Manish Joshi, Pawan Lingras
Evolutionary and Iterative Crisp and Rough Clustering I: Theory. PReMI (2009)
Cory J. Butz, Pawan Lingras, Ken Konkel
A Web-Based Interface for Hiding Bayesian Network Inference. ISMIS (2008)
Pawan Lingras, Min Chen, Duoqian Miao
Rough Multi-category Decision Theoretic Framework. RSKT (2008)
Pawan Lingras, Min Chen, Duoqian Miao
Precision of Rough Set Clustering. RSCTC (2008)
Keith Bain, Jason Hines, Pawan Lingras, Yumei Qin
Using Speech Recognition and Intelligent Search Tools to Enhance Information Accessibility. HCI (7) (2007)
Pawan Lingras, Rucha Lingras
Adaptive hyperlinks Using Page Access Sequences and Minimum Spanning Trees. FUZZ-IEEE (2007)
Pawan Lingras, Cory J. Butz
Precision and Recall in Rough Support Vector Machines. GrC (2007)
Pawan Lingras
Applications of Rough Set Based K-Means, Kohonen SOM, GA Clustering. Trans. Rough Sets 7 (2007)
Pawan Lingras, Richard Jensen
Survey of Rough and Fuzzy Hybridization. FUZZ-IEEE (2007)
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) (2007)
Ravipriya Ranatunga, Sisil Kumarawadu, Pawan Lingras, Tsu-Tian Lee
A New Paradigm for Intelligent Collision Avoidance via Interactive and Interdependent Generic Maneuvers. SMC (2006)
Pawan Lingras, Cory J. Butz
Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiers. RSFDGrC (2) (2005)
Pawan Lingras, Cory J. Butz
Interval set representations of 1-v-r support vector machine multi-classifiers. GrC (2005)
Pawan Lingras, Mofreh Hogo, Miroslav Snorek, Chad West
Temporal analysis of clusters of supermarket customers: conventional versus interval set approach. Inf. Sci. 172 (1-2) (2005)
Cory J. Butz, Pawan Lingras
On the Practical Irrelevance of Diverging Implication between Probabilistic Conditional Independence and Embedded Multivalued Dependency. IICAI (2005)
Pawan Lingras, Xiandong Huang
Statistical, Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based Approaches. Artif. Intell. Rev. 23 (1) (2005)
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) (2005)
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) (2004)
Pawan Lingras, Chad West
-Means. J. Intell. Inf. Syst. 23 (1) (2004)
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)

Pawan Lingras.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Pawan Lingras