Pawan Lingras - researchr alias

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2011

Advances in Artificial Intelligence - 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John s, Canada, May 25-27, 2011. ProceedingsCory J. Butz, Pawan Lingras, editors, Volume 6657 of Lecture Notes in Computer Science, Springer, 2011. [doi]

Rough clusteringPawan Lingras, Georg Peters. widm, 1(1):64-72, 2011. [doi]

Classification with Dynamic Reducts and Belief FunctionsSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. trs, 14:202-233, 2011. [doi]

Use of Stability and Seasonality Analysis for Optimal Inventory Prediction ModelsPeng Zhang, Manish Joshi, Pawan Lingras. jois, 20(2):147-166, 2011. [doi]

2010

Active Media Technology, 6th International Conference, AMT 2010, Toronto, Canada, August 28-30, 2010. ProceedingsAijun An, Pawan Lingras, Sheila Petty, Runhe Huang, editors, Volume 6335 of Lecture Notes in Computer Science, Springer, 2010. [doi]

The CPT Structure of Variable Elimination in Discrete Bayesian NetworksCory J. Butz, W. Yan, Pawan Lingras, Y. Y. Yao. In Zbigniew W. Ras, Li-Shiang Tsay, editors, Advances in Intelligent Information Systems. Volume 265 of Studies in Computational Intelligence, pages 245-257, Springer, 2010. [doi]

Rough, fuzzy, interval clustering for web usage miningManish Joshi, Pawan Lingras, Yiyu Yao, Virendrakumar C. Bhavsar. isda 2010: 397-402 [doi]

Analysis of Rough and Fuzzy ClusteringManish Joshi, Pawan Lingras, C. Raghavendra Rao. rskt 2010: 679-686 [doi]

Rough support vector regressionPawan Lingras, Cory J. Butz. eor, 206(2):445-455, 2010. [doi]

Transactions on Rough Sets XIIJames F. Peters, Andrzej Skowron, Roman Slowinski, Pawan Lingras, Duoqian Miao, Shusaku Tsumoto, editors, Volume 6190 of Lecture Notes in Computer Science, Springer, 2010. [doi]

A Comparison of Dynamic and Static Belief Rough Set ClassifierSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. rsctc 2010: 366-375 [doi]

Belief Rough Set Classification for web mining based on dynamic coreSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. isda 2010: 403-408 [doi]

Rule Discovery Process Based on Rough Sets under the Belief Function FrameworkSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. ipmu 2010: 726-736 [doi]

Rough Set and Knowledge Technology - 5th International Conference, RSKT 2010, Beijing, China, October 15-17, 2010. ProceedingsJian Yu, Salvatore Greco, Pawan Lingras, Guoyin Wang, Andrzej Skowron, editors, Volume 6401 of Lecture Notes in Computer Science, Springer, 2010. [doi]

2009

Join Tree Propagation Utilizing Both Arc Reversal and Variable EliminationCory J. Butz, Ken Konkel, Pawan Lingras. flairs 2009:

A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network InferenceCory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras. flairs 2009:

A formal comparison of variable elimination and arc reversal in Bayesian network inferenceCory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras. idt, 3(3):173-180, 2009. [doi]

Rough Set Year in India 2009Manish Joshi, Rabi N. Bhaumik, Pawan Lingras, Nitin Patil, Ambuja Salgaonkar, Dominik Slezak. rsfdgrc 2009: 67-68 [doi]

Evolutionary and Iterative Crisp and Rough Clustering II: ExperimentsManish Joshi, Pawan Lingras. premi 2009: 621-627 [doi]

Evolutionary and Iterative Crisp and Rough Clustering I: TheoryManish Joshi, Pawan Lingras. premi 2009: 615-620 [doi]

An Algorithm for the Estimation of a Time Period of 2-SequencesManish Joshi, Virendrakumar C. Bhavsar, Pawan Lingras. iicai 2009: 71-88

Evolutionary Rough K-Means ClusteringPawan Lingras. rskt 2009: 68-75 [doi]

Rough K-medoids clustering using GAsPawan Lingras. IEEEicci 2009: 315-319 [doi]

Semi-supervised Rough Cost/Benefit DecisionsPawan Lingras, Min Chen, Duoqian Miao. FUIN, 94(2):233-244, 2009. [doi]

Rough Cluster Quality Index Based on Decision TheoryPawan Lingras, Min Chen, Duoqian Miao. tkde, 21(7):1014-1026, 2009. [doi]

Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009, Tumkur, Karnataka, India, December 16-18, 2009Bhanu Prasad, Pawan Lingras, Ashwin Ram, editors, IICAI, 2009.

Belief Rough Set ClassifierSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. ai 2009: 257-261 [doi]

Dynamic Reduct from Partially Uncertain Data Using Rough SetsSalsabil Trabelsi, Zied Elouedi, Pawan Lingras. rsfdgrc 2009: 160-167 [doi]

Interval Set Cluster Analysis: A Re-formulationYiyu Yao, Pawan Lingras, Ruizhi Wang, Duoqian Miao. rsfdgrc 2009: 398-405 [doi]

2008

Building an intelligent web - theory and practice: contains IBM DB2 Express-C9Rajendra Akerkar, Pawan Lingras. Jones and Bartlett Publishers, 2008.

A Web-Based Interface for Hiding Bayesian Network InferenceCory J. Butz, Pawan Lingras, K. Konkel. ismis 2008: 612-617 [doi]

Evolutionary Regression and Neural Imputations of Missing ValuesPawan Lingras, Ming Zhong, Satish Sharma. In Bhanu Prasad, editor, Soft Computing Applications in Industry. Volume 226 of Studies in Fuzziness and Soft Computing, pages 151-163, Springer, 2008. [doi]

Precision of Rough Set ClusteringPawan Lingras, Min Chen, Duoqian Miao. rsctc 2008: 369-378 [doi]

Rough Multi-category Decision Theoretic FrameworkPawan Lingras, Min Chen, Duoqian Miao. rskt 2008: 676-683 [doi]

2007

Using Speech Recognition and Intelligent Search Tools to Enhance Information AccessibilityKeith Bain, Jason Hines, Pawan Lingras, Yumei Qin. hci 2007: 214-223 [doi]

Precision and Recall in Rough Support Vector MachinesPawan Lingras, Cory J. Butz. grc 2007: 654-658 [doi]

Adaptive hyperlinks Using Page Access Sequences and Minimum Spanning TreesPawan Lingras, Rucha Lingras. fuzzIEEE 2007: 1-6 [doi]

Survey of Rough and Fuzzy HybridizationPawan Lingras, Richard Jensen. fuzzIEEE 2007: 1-6 [doi]

Applications of Rough Set Based K-Means, Kohonen SOM, GA ClusteringPawan Lingras. trs, 7:120-139, 2007. [doi]

Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classificationPawan Lingras, Cory J. Butz. isci, 177(18):3782-3798, 2007. [doi]

Rough Sets and Knowledge Technology, Second International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007, ProceedingsJingtao Yao, Pawan Lingras, Wei-Zhi Wu, Marcin S. Szczuka, Nick Cercone, Dominik Slezak, editors, Volume 4481 of Lecture Notes in Computer Science, Springer, 2007.

2005

On the Practical Irrelevance of Diverging Implication between Probabilistic Conditional Independence and Embedded Multivalued DependencyCory J. Butz, Pawan Lingras. iicai 2005: 2464-2475

Interval set representations of 1-v-r support vector machine multi-classifiersPawan Lingras, Cory J. Butz. grc 2005: 193-198 [doi]

Reducing the Storage Requirements of 1-v-1 Support Vector Machine Multi-classifiersPawan Lingras, Cory J. Butz. rsfdgrc 2005: 166-173 [doi]

Statistical, Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based ApproachesPawan Lingras, Xiandong Huang. air, 23(1):3-29, 2005. [doi]

Temporal analysis of clusters of supermarket customers: conventional versus interval set approachPawan Lingras, Mofreh Hogo, Miroslav Snorek, Chad West. isci, 172(1-2):215-240, 2005. [doi]

Relationship between Product Based Loyalty and Clustering based on Supermarket Visit and Spending PatternsChad West, Stephanie MacDonald, Pawan Lingras, Greg Adams. ijcsa, 2(2):85-100, 2005. [doi]

2004

Temporal Versus Latest Snapshot Web Usage Mining Using Kohonen Som And Modified Kohonen Som Based on The Properties of Rough Sets TheoryMofreh Hogo, Miroslav Snorek, Pawan Lingras. ijait, 13(3):569-592, 2004. [doi]

Interval Set Clustering of Web Users with Rough ::::K::::-MeansPawan Lingras, Chad West. jiis, 23(1):5-16, 2004. [doi]

Temporal Cluster Migration Matrices for Web Usage MiningPawan Lingras, Mofreh Hogo, Miroslav Snorek. webist 2004: 441-444 [doi]

Interval set clustering of web users using modified Kohonen self-organizing maps based on the properties of rough setsPawan Lingras, Mofreh Hogo, Miroslav Snorek. wias, 2(3):217-225, 2004. [doi]

Web-based Support Systems (WSS): A Report of the WIC Canada Research CentreYiyu Yao, Jingtao Yao, Cory J. Butz, Pawan Lingras, Dawn N. Jutla. webist 2004: 787-788 [doi]

Analyzing the Performance of Genetically Designed Short-Term Traffic Prediction Models Based on Road Types and Functional ClassesMing Zhong, Satish Sharma, Pawan Lingras. ieaaie 2004: 1133-1145 [doi]

2003

Genetic algorithms for rerouting shortest paths in dynamic and stochastic networksCedric Davies, Pawan Lingras. eor, 144(1):27-38, 2003. [doi]

Conventional Versus Interval Clustering Using Kohonen NetworksMofreh Hogo, Pawan Lingras, Miroslav Snorek. ICEIS 2003: 250-257

Temporal Web Usage MiningMofreh Hogo, Miroslav Snorek, Pawan Lingras. webist 2003: 450-453 [doi]

Comparison of Conventional and Rough K-Means ClusteringPawan Lingras, Rui Yan, Chad West. rsfdgrc 2003: 130-137 [doi]

Clustering Supermarket Customers Using Rough Set Based Kohonen NetworksPawan Lingras, Mofreh Hogo, Miroslav Snorek, Bill Leonard. ismis 2003: 169-173 [doi]

Rough Set Based Clustering: Evolutionary, Neural, and Statistical ApproachesPawan Lingras, Rui Yan, Mofreh Hogo. iicai 2003: 1074-1087

Fuzzy C-Means Clustering of Web Users for Educational SitesPawan Lingras, Rui Yan, Chad West. ai 2003: 557-562 [doi]

Clustering of Web Users: K-Means vs. Fuzzy C-MeansPawan Lingras, Rui Yan, Adish Jain. iicai 2003: 1062-1073

Supermarket Customer Attrition Analysis Based on Cluster Membership PatternsChad West, Adish Jain, Pawan Lingras, Bill Leonard. iicai 2003: 1132-1140

2002

Time Complexity of Rough Clustering: GAs versus K-MeansPawan Lingras, Y. Y. Yao. rsctc 2002: 263-270 [doi]

2001

Fuzzy-rough and rough-fuzzy serial combinations in neurocomputingPawan Lingras. ijon, 36(1-4):29-44, 2001. [doi]

Time Delay Neural Networks Designed Using Genetic Algorithms for Short Term Inter-City Traffic ForecastingPawan Lingras, Paul Mountford. ieaaie 2001: 290-299 [doi]

Application of Rough Genetic AlgorithmsPawan Lingras, Cedric Davies. ci, 17(3):435-445, 2001.

Unsupervised Rough Set Classification Using GAsPawan Lingras. jiis, 16(3):215-228, 2001.

1999

Rough Genetic AlgorithmsPawan Lingras, Cedric Davies. rsfdgrc 1999: 38-46

1998

Comparison of Neofuzzy and Rough Neural NetworksPawan Lingras. isci, 110(3-4):207-215, 1998.

Data Mining Using Extensions of the Rough Set ModelPawan Lingras, Y. Y. Yao. jasis, 49(5):415-422, 1998.

Interpretation of Belief Functions in The Theory of Rough SetsY. Y. Yao, Pawan Lingras. isci, 104(1-2):81-106, 1998.

1994

Representation of Qualitative User Preference by Quantitative Belief FunctionsS. K. Michael Wong, Pawan Lingras. tkde, 6(1):72-78, 1994. [doi]

1993

Upper and Lower Entropies of Belief Functions Using Compatible Probability FunctionsC. W. R. Chau, Pawan Lingras, S. K. Michael Wong. ismis 1993: 306-315

Combination of Evidence in Rough Set TheoryPawan Lingras. icci 1993: 289-293

1991

Propagation of Preference Relations in Qualitative Inference NetworksS. K. Michael Wong, Pawan Lingras, Yiyu Yao. IJCAI 1991: 1204-1209

Compatibility of Quantitative and Qualitative Representations of BeliefS. K. Michael Wong, Yiyu Yao, Pawan Lingras. uai 1991: 418-424 [doi]

Towards Implementing Valuation Based Systems with Relational DatabasesS. K. Michael Wong, Pawan Lingras, Yiyu Yao. ismis 1991: 172-182

1990

Two Perspectives of the Dempster-Shafer Theory of Belief FunctionsPawan Lingras, S. K. Michael Wong. ijmms, 33(4):467-487, 1990.

1988

An Optimistic Rule for Accumulation of EvidencePawan Lingras, S. K. Michael Wong. ismis 1988: 60-69