Recent Publications (In Reverse Chronological Order)

    2024

  1. J.T Yao and A. Sharma, Continual Federated Learning for Dynamic Data Environments, PACRIM'24, No. 10690192, 2024.
  2. M.J. Hu, C. Cornelis, Y. Zhang, P. Lingras, D. Slezak, J.T. Yao, Proceedings of the International Joint Conference on Rough Sets (IJCRS 2024), Part I, Halifax, NS, Canada, May 17-20, 2024, LNAI 14839, Springer, 2024.
  3. M.J. Hu, C. Cornelis, Y. Zhang, P. Lingras, D. Slezak, J.T. Yao, Proceedings of the International Joint Conference on Rough Sets (IJCRS 2024), Part II, Halifax, NS, Canada, May 17-20, 2024, LNAI 14840, Springer, 2024.
  4. A.Chouhan and J.T Yao, Privacy-Preserving Federated Learning: Insights and Perspectives, Book of Abstracts, IJCRS'24, pp.6-9, 2024.
  5. C.Q.Li, J.T. Yao, Incorporating Game Theory with Soft Sets, ICNC 2024, pp. 334-339, 2024.
  6. H. Yu, J. Wang, S.-Y. Zhao, O. Silver, Z. Liu. J.T. Yao, J.-Y. Shi, GGI-DDI: Identification for key molecular substructures by granule learning to interpret predicted drug-drug interactions, Expert Systems with Applications, 240:122500, 2024.

    2023

  7. A. Campagner, O. Lenz, S.Y. Xia, D. Slezak, J. Was, J.T. Yao, Proceedings of the International Joint Conference on Rough Sets (IJCRS 2023), Krakow, Poland, Oct 5-8, 2023, LNAI 14481, Springer, 2023.
  8. Y.Y. Yao, J.T. Yao, Cognitive and Social Decision Making: Three-Way Decision Perspectives, IJCRS 2023, LNAI 14481, pp.259-269, 2023.
  9. J.T. Yao, Three-way Clustering: An Advanced Soft Clustering Approach, IEEE CSCI 2023, pp113-118, 2023.
  10. J.T. Yao, C. Cornelis, G.Y. Wang and Y.Y. Yao, Uncertainty and three-way decision in data science, International Journal of Approximate Reasoning, 162:109024, 2023.
  11. D.B. Chakraborty and J.T. Yao, Event Prediction with Rough-Fuzzy Sets, Pattern Analysis and Applications, 26:691-701, 2023.

    2022

  12. A. Shah, N. Azam, E. Alanazi, J.T. Yao, Image Blurring and Sharpening Inspired Three-way Clustering Approach, Applied Intelligence,52:18131-18155, 2022.
  13. J.T. Yao, Y.Y Yao, D. Ciucci, K.Z. Huang, Granular Computing and Three-way Decisions for Cognitive Analytics, Cognitive Computation, 14(6):1801-1804, 2022.
  14. J.T. Yao, H. Fujita, X.D. Yue, D.Q. Miao, J. Grzymala-Busse, F.Z. Li, Proceedings of the International Joint Conference on Rough Sets (IJCRS 2022), Suzhou, China, Nov 11-14, 2022, LNAI 13633, Springer, 2022.
  15. C.M. Jiang, Z.C. Li, J.T. Yao, A shadowed set-based three-way clustering ensemble approach, International Journal of Machine Learning and Cybernetics, 13(9):2545-2558, 2022.
  16. B. Ali, N. Azam, J.T. Yao, A three-way clustering approach using image enhancement operations, International Journal of Approximate Reasoning, 149:1-38, 2022.
  17. J.T. Yao, J. Medina, Y. Zhang, D. Slezak, Formal concept analysis, rough sets, and three-way decisions, International Journal of Approximate Reasoning, 140:1-6, 2022.

    2021

  18. S. Singh, J.T. Yao, Pneumonia Detection with Game-theoretic Rough Sets, IEEE ICMLA 2021, pp1029-1034 (acceptance rate 25.74%)
  19. Y.X. Chen, J.T. Yao, Sentiment Analysis Using Part-of-Speech-Based Feature Extraction and Game-Theoretic Rough Sets, SENTIRE 2021, ICDMW, pp110-117.
  20. A. Shah, N. Azam, B. Ali, M.T. Khan, J.T. Yao, A Three-way Clustering Approach for Novelty Detection, Information Sciences, 569:650-668, 2021.
  21. B. Ali, N. Azam, A. Shah, J.T. Yao, A spatial filtering inspired three-way clustering approach with application to outlier detection, International Journal of Approximate Reasoning, 130:1-21, 2021.
  22. H. Yu, L.Y. Chen, J.T. Yao, A three-way density peak clustering method based on evidence theory, Knowledge-Based Systems, 211:106532, 2021.

    2020

  23. Y. Zhou, Y. Zhang, and J.T. Yao, Satirical News Detection with Semantic Feature Extraction and Game-Theoretic Rough Sets, ISMIS 2020, LNCS 12117, 123-135.
  24. X. Cui, J.T. Tao, and Y. Y. Yao, Modeling Use-Oriented Attribute Importance with the Three-Way Decision Theory, IJCRS 2020, LNAI 12179, pp122-136.
  25. Y. Zhang, Y. Zhou, J.T. Yao Feature Extraction with TF-IDF and Game-Theoretic Shadowed Sets, IPMU 2020, CCIS 1237, pp722-733.
  26. M.K. Afridi, N. Azam, J.T. Yao, Variance based Three-way Clustering Approaches for Handling Overlapping Clustering, International Journal of Approximate Reasoning, 118:47-63, 2020.
  27. Y. Zhang and J.T. Yao, Game Theoretic Approach to Shadowed Sets: A Three-way Tradeoff Perspective, Information Sciences, 507:540-552, 2020. (WoS highly cited paper)

    2019

  28. S.S. Ribeiro and J.T. Yao, Three-way Image Classification Model: A Case Study on Corn Grain Images, The 21st IEEE International Symposium on Multimedia, Dec 9-11, 2019, San Diego, USA, pp177-183.
  29. S.S. Ribeiro, D.A. Rezende and J.T. Yao, Toward a model of the municipal evidence-based decision process in the strategic digital city context, Information Polity, 23(3):305-324, 2019.
  30. H. Yu, L.Y. Chen, J.T. Yao and X.N. Wang, A three-way clustering method based on an improved DBSCAN algorithm, Physica A, 535:122289, 2019.
  31. J.T. Yao, The Impact of Rough Set Conferences, IJCRS 2019, LNCS 11499, pp383-394.
  32. Y. Zhang, P.F. Liu and J.T. Yao, Three-way Email Spam Filtering with Game-theoretic Rough Sets, ICNC 2019, pp. 542-546.

    2018

  33. S. Ribeiro, J.T. Yao, and D. Rezende, Discovering IMRaD Structure with Different Classifiers, ICBK 2018, X.D. Wu et. al (eds) pp. 200-204.
  34. B.Y. Li and J.T. Yao, Exploring GTRS Based Recommender Systems with Users of Different Rating Patterns , IJCRS 2018, LNCS 11103, pp405-417.
  35. N. Azam, M.K. Afrid, and J.T. Yao, A Game-Theoretic Rough Set Approach for Handling Missing Data in Clustering, IEA/AIE 2018, LNCS 10868, pp635-647.
  36. Y. Zhang and J.T. Yao, Determining Strategies in Game-Theoretic Shadowed Sets, IPMU 2018, CCIS 854, pp 736-747,
  37. M.K. Afridi, N. Azam, J.T. Yao and E. Alanazi, A Three-way Clustering Approach for Handling Missing Data using GTRS, International Journal of Approximate Reasoning (IF 2.845, Q1), 98:11-24, 2018.

    2017

  38. S. Bandyopadhyay, J.T. Yao and Y. Zhang, Granular Computing with Compatibility Based Intuitionistic Fuzzy Rough Sets, IEEE ICMLA 2017, pp378-383, 2017.
  39. S. Bandyopadhyay and J.T. Yao, A Decision Support System for Cancer Differentiation Therapy with Game-Theoretic Rough Sets, IEEE SMC 2017, pp710-715, 2017.
  40. J.T. Yao, O.A. Oladimeji, and Y. Zhang, Fractal Analysis Approaches to Granular Computing, In: Polkowski L. et al. (eds): IJCRS 2017, LNCS 10313 pp 215-222, 2017.
  41. Y. Zhang and J.T. Yao, Multi-criteria based Three-way Classifications with Game-theoretic Rough Sets, In: Kryszkiewicz M. et al. (eds): ISMIS 2017, LNCS 10352, pp 550-559, 2017.
  42. J.T. Yao and A. Onasanya, Recent Development of Rough Computing: A Scientometrics View, in G. Wang et al. (eds.), Thriving Rough Sets, Studies in Computational Intelligence 708, pp21-45, 2017.
  43. N. Azam, Y. Zhang and J.T. Yao, Evaluation Functions and Decision Conditions of Three-way Decisions with Game-theoretic Rough Sets, European Journal of Operational Research (IF 2.679, Q1), 261(2):704-714, 2017.
  44. H.U. Rehman, N. Azam, J.T. Yao, and A. Benso, A Three-way Approach for Protein Function Classification, PLoS ONE (IF 3.54, Q1), 12(2):e0171702, 2017.
  45. M.T. Khan, N. Azam, S. Khalid and J.T. Yao, A Three-way Approach for Learning Rules in Automatic Knowledge-based Topic Models, International Journal of Approximate Reasoning (IF 2.696, Q1), 82:210-226, 2017.
  46. Y. Zhang and J.T. Yao, Gini Objective Functions for Three-way Classifications, International Journal of Approximate Reasoning (IF 2.696, Q1), 81:103-114, 2017.

    2016

  47. N. Azam, and J.T. Yao, Variance based Interpretation of Three-way Decisions Using Probabilistic Rough Sets, V. Flores et al. (Eds.): IJCRS 2016, LNAI 9920, pp.209-218, 2016.
  48. Y. Zhang and J.T. Yao, Towards Coordination Game Formulation in Game-theoretic Rough Sets, V. Flores et al. (Eds.): IJCRS 2016, LNAI 9920, pp.155-165, 2016.
  49. M. Nauman, N. Azam, and J.T. Yao, A Three-way Decision Making Approach to Malware Analysis Using Probabilistic Rough Sets, Information Sciences (IF 3.36, Q1), 374:193-209, 2016.

    2015

  50. H. Yu, et al.(J.T. Yao), Methods and Practices of Three-Way Decisions for Complex Problem Solving, RSKT 2015: LNAI 9436, Springer, pp 255-265, 2015
  51. M. Nauman, N. Azam, and J.T. Yao, A Three-Way Decision Making Approach to Malware Analysis, D. Ciucci et al. (Eds.): RSKT 2015, LNAI 9436, Springer, pp273-284, 2015.
  52. Y. Zhang and J.T. Yao, Determining Three-Way Decision Regions by Combining Gini Objective Functions and GTRS, Y. Yao et al. (Eds.): RSFDGrC 2015, LNAI 9437, Springer, pp392-403, 2015.
  53. J.T. Yao, D. Ciucci, & Y. Zhang, Generalized Rough Sets, Chapter 25, The Springer Handbook of Computational Intelligence, Kacprzyk, Pedrycz (Eds.), Springer, pp413-424, 2015.
  54. J.T. Yao, N. Azam, Web-based Medical Decision Support Systems for Three-way Medical Decision Making with Game-theoretic Rough Sets, IEEE Transactions on Fuzzy Systems (IF6.3, Q1), 23(1):3-15, 2015. (WoS highly cited paper)
  55. N. Azam, J. T. Yao, Interpretation of Equilibria in Game-theoretic Rough Sets, Information Sciences (IF 3.89, Q1), 295:586-599, 2015.

    2014

  56. N. Azam, J.T. Yao, Game-theoretic Rough Sets for Recommender Systems, Knowledge-Based Systems (IF3.0, Q1), 72:96-107, 2014.
  57. N. Azam, J. T. Yao, Application of Game-theoretic Rough Sets for Recommender Systems, in M.N. Murty et al. (Eds.): MIWAI 2014, LNCS (LNAI) 8875, pp.89-100, 2014.
  58. T.R. Li, H.M. Chen, J.T. Yao, and H.S. Nguyen, Advances on Rough Sets and Knowledge Technology (preface), Fundamenta Informaticae, 132(3), i-iii, 2014.
  59. B. Majeed, N. Azam, J.T. Yao, Thresholds Determination for Probabilistic Rough Sets with Genetic Algorithms, in D. Miao et al. (Eds.): RSKT 2014, LNAI 8818, pp. 693-704, 2014.
  60. Y. Zhou, J.T. Yao, A Web-Based Learning Support System for Rough Sets, in D. Miao et al. (Eds.): RSKT 2014, LNAI 8818, pp. 161-172, 2014.
  61. J.F. Peters, A. Skowron, T.R. Li, Y. Yang, J.T. Yao, and H.S. Nguyen (eds.), JRS 2012 Special Issue, Transactions on Rough Sets, Volume XVIII, LNCS 8449, 2014.
  62. Y. Zhang, J.T. Yao, Determining Three-Way Decision Regions with Gini Coefficients, in C. Cornelis et al. (Eds.): RSCTC 2014, LNCS(LNAI) 8536, pp160-171, 2014.
  63. X.F. Deng, Y.Y. Yao, J.T. Yao, On Interpreting Three-Way Decisions through Two-Way Decisions, in T. Andreasen et al. (Eds.): ISMIS 2014, LNCS(LNAI) 8502, pp73-82, 2014.
  64. N. Azam, J.T. Yao, Analyzing Uncertainties of Probabilistic Rough Set Regions with Game-theoretic Rough Sets, International Journal of Approximate Reasoning (IF1.9, Q1), 55(1):142-155, 2014.
  65. J.T. Yao, H.X. Li, G. Peters, Decision-theoretic rough sets and beyond, International Journal of Approximate Reasoning (IF1.9, Q1), 55(1):99-100, 2014.

    2013

  66. J.T. Yao, N. Azam, Incorporating Game-theoretic Rough Sets in Web-based Medical Decision Support Systems, 2013 12th International Conference on Machine Learning and Applications, Miami, Florida, USA, December 4-7, 2013, Volumn 2, 335-338.
  67. J.T. Yao, A.V. Vasilakos and W. Pedrycz, Granular Computing: Perspectives and Challenges, IEEE Transactions on Cybernetics, 43(6):1977-1989, 2013. (WoS Highly cited paper)
  68. J.T. Yao, A. Skowron, G.Y. Wang, H.S. Nguyen, Rough Sets and Knowledge Technology 2011, Preface, Fundamenta Informaticae, 126(4):i-iii, 2013.
  69. N. Azam, J.T. Yao, Formulating Game Strategies in Game-Theoretic Rough Sets, in P. Lingras et al. (Eds.): RSKT 2013, LNCS(LNAI) 8171, pp145-153, 2013.
  70. J.T. Yao, Y. Zhang, A Scientometrics Study of Rough Sets in Three Decades, in P. Lingras et al. (Eds.): RSKT 2013, LNCS(LNAI) 8171, pp28-40, 2013.
  71. N. Azam, J.T. Yao, On semantic issues in game-theoretic rough sets, 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), Edmonton, Canada June 24-28, 2013, pp.1303-1308.
  72. J.T. Yao, A. Dinh, M. Mehrandezh, R. Paranjape, and C. Gelowitz (Eds.), The Proceedings of 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2013), May 5-8, 2013 Regina, Saskatchewan, Canada. (Preface)
  73. L. Benedicenti, D.Y. Blachford, C. Chan, A. East, C. Gelowitz, G. Huang, R. Paranjape, S. Petty, J.T. Yao, and Y.Y. Yao, Multidisciplinary approaches to computing, Proceedings of CCECE 2013, pp.16-23.
  74. S. J. Kim, J.T. Yao, Mobile research support systems, Proceedings of CCECE 2013, pp.766-770.
  75. N. Azam, J. T. Yao, Game-theoretic Rough Sets for Feature Selection, in Skowron and Suraj (Eds.), Rough Sets and Intelligent Systems - Professor Zdzislaw Pawlak in Memoriam (Volume 2), Intelligent Systems Reference Library, Vol. 43, pp.61-78, 2013.

    2012

  76. Y. Zhang, J.T. Yao, Rule Measures Tradeoff Using Game-theoretic Rough Sets, in F.M. Zanzotto et al. (Eds.), Proceedings of the International Conference on Brian Informatics (BI'12), Macau, China, Dec 4-7, 2012, LNCS 7670, pp.348-359.
  77. N. Azam, J. T. Yao, Multiple Criteria Decision Analysis with Game-Theoretic Rough Sets, Proceedings of the 6th International Conference on Rough Set and Knowledge Technology, RSKT 2012, Chengdu, China, August 17-20, 2012, LNCS 7414, pp.399-408.
  78. J.T. Yao, Y. Yang, R. Slowinski, S. Greco, H.X. Li, S. Mitra, and L. Polkowski (Eds), Proceedings of the 8th International Conference on Rough Sets and Current Trends in Computing, Chengdu, China, August 17-20, 2012, LNCS 7413, Springer-Verlag, Berlin Heidelberg 2012.
  79. N. Azam, J. T. Yao, Classifying Attributes with Game-theoretic Rough Sets, in Watada, Watanabe, Phillips-Wren, Howlett and Jain (Eds.), Proceedings of the 4th International Conference on Intelligent Decision Technologies (IDT'12), Gifu, Japan, May 23-25, 2012, Smart Innovation, Systems and Technologies, Vol. 15, pp.175-184
  80. X.P. Yang and J.T. Yao, Modelling Multi-agent three-way Decisions with Decision-theoretic Rough Sets, Fundamenta Informaticae, 115(2-3):157-171, 2012.
  81. N. Azam and J.T. Yao, Comparison of Term Frequency and Document Frequency Based Feature Selection Metrics in Text Categorization, Expert Systems with Applications, 39(5):4760-4768, 2012.

    2011

  82. J.T. Yao, S. Ramanna, G.Y. Wang and Z. Suraj (Eds), Rough Set and Knowledge Technology, the 6th International Conference, RSKT 2011, Banff, Canada, Oct 9-12, 2011, LNCS(LNAI) 6954, Springer-Verlag, Berlin Heidelberg 2011.
  83. J. P. Herbert and J.T. Yao, Analysis of Data-Driven Parameters in Game-Theoretic Rough Sets, RSKT 2011, Banff, Canada, Oct 9-12, 2011, LNCS(LNAI) 6954, pp.447-456, 2011.
  84. N. Azam and J.T. Yao, Incorporating Game Theory in Feature Selection for Text Categorization, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, LNCS(LNAI) 6743, pp215-222.
  85. J.P. Herbert, J.T. Yao, Game-theoretic Rough Sets, Fundamenta Informaticae, 108(3-4):267-286, 2011.

    2010

  86. D.W. Kim, J.T. Yao, A Treasure Hunt Model for Inquiry-based Learning in the Development of a Web-based Learning Support System, Journal of Universal Computer Science, 16(14):1853-1881, 2010.
  87. X.P. Yang, J.T. Yao, A Multi-agent Decision-theoretic Rough Set Model, Proceedings of Rough Sets and Knowledge Technology (RSKT'10), Beijing, China, Oct.15-17, 2010, LNAI 6401, pp.711-718.
  88. D.W. Kim, J.T. Yao, A Web-Based Learning Support System for Inquiry-Based Learning, J.T. Yao (eds.), Web-Based Support Systems, London: Springer-Verlag, 2010, pp125-143.

    2009

  89. J. P. Herbert, J.T. Yao, A granular computing framework for self-organizing maps, Neurocomputing, 72(13-15):2865-2872, 2009.
  90. J.P. Herbert, J.T. Yao, Learning Optimal Parameters in Decision-Theoretic Rough Sets, Proceedings of Rough Sets and Knowledge Technology (RSKT'09), Gold Coast, Australia, July 14-16, 2009, LNAI 5589, pp610-617. (Best student paper award)
  91. J.T. Yao, J.P. Herbert, Financial Time-series Ana lysis with Rough Sets, Applied Soft Computing, 9(3):1000-1007, 2009.
  92. Y. Wang, K.L. Wang, J. T. Yao, Marketing mixes for digital products: a study of the marketspaces in China, International Journal of Technology Marketing, 4(1):15-42, 2009.
  93. J. P. Herbert, J.T. Yao, Criteria for Choosing a Rough Set Model, Computers and Mathematics with Applications, 57(6):908-918, 2009.

    2008

  94. J.T. Yao, V.V. Raghavan, Z.H. Wu, Web information fusion: A review of the state of the art, Information Fusion, Vol. 9, No 4, 446-449, 2008.
  95. J.T. Yao, V.V. Raghavan, Z.H. Wu, Web Information Fusion (Editorial), Information Fusion, Vol.9, No 4, 444-445, 2008.
  96. J. T. Yao, Y. Y. Yao, W. Ziarko, Probabilistic rough sets: Approximations, decision-makings, and applications (Editorial), International Journal of Approximate Reasoning, Vol. 49, No. 2, 253-254, 2008.
  97. J.T. Yao, Recent Developments in Granular Computing: A Bibliometrics Study (Invited Plenary Speech), IEEE International Conference on Granular Computing, Hangzhou, China, Aug 26-28, 2008, pp74-79.
  98. J.T. Yao, Granular Computing: A New Paradigm in Information Processing (Invited Speaker), North American Simulation Technology Conference 2008 (NASTEC'08), Montreal, Canada August 13-15, 2008, pp5-6.
  99. J. T. Yao, Y.Y. Yao, V. Kreinovich, P. Pinheiro da Silva, S.A. Starks, X. Gang and H.T. Nguyen, Towards More Adequate Representation of Uncertainty: From Intervals to Set Intervals, with the Possible Addition of Probabilities and Certainty Degrees, Proceedings of 2008 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2008), Hong Kong, June 1-6, 2008, pp983-990.
  100. J. P. Herbert, J.T. Yao, Game-Theoretic Risk Analysis in Decision-Theoretic Rough Sets, Proceedings of the 3rd International Conference on Rough Sets and Knowledge Technology (RSKT'08), May 17-19, 2008, Chengdu, China, LNAI 5009, pp132-139.
  101. J.T. Yao, J.P. Herbert, A Game-Theoretic Perspective on Rough Set Analysis, 2008 International Forum on Knowledge Technology (IFKT'08), Chongqing, Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), Vol. 20, No. 3, pp291-298, 2008.
  102. J. T. Yao, An Introduction to Web-based Support Systems, Journal of Intelligent Systems, Vol. 17, No. 1-3, pp267-281, 2008.

    2007

  103. J. P. Herbert, J.T. Yao, Growing Hierarchical Self-Organizing Maps for Web Mining, Profeedings of 2007 IEEE/WIC/ACM International Conference on Web Intelligence, Sillicon Valley, CA, USA, Nov 2-5, 2007, pp299-302.
  104. J. T. Yao A Ten-Year Review of Granular Computing, Proceedings of 2007 IEEE International Conference on Granular Computing, Sillicon Valley, CA, USA, Nov 2-4, 2007, pp734-739.
  105. J. P. Herbert, J.T. Yao, Rough Set Model Selection for Practical Decision Making, Proceedings of the 4th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'07), Aug 24-27, 2007, Hainan, China, III, pp203-207.
  106. J.S. Lei, J.T. Yao, Q.F. Zhang, (eds) Proceedings of the 3rd International Conference on Natural Computation (ICNC'07), I, II, III, IV, and V, Haikou, China, Aug 24 - 27, 2007, IEEE Press. (ISBN: 0-7695-2875-9)
  107. J.T. Yao, J.P. Herbert, Web-based Support Systems with Rough Set Analysis, Proceedings of International Conference on Rough Sets and Emerging Intelligent System Paradigms (RSEISP'07), June 28-30, 2007, Warsaw, Poland, LNAI 4585, pp 360-370.
  108. J. T. Yao, P. Lingras, W.-Z. Wu, M. Szczuka, N. Cercone, D. Slezak (Eds.), Proceedings of the 2nd International Conference on Rough Sets and Knowledge Technology (RSKT'07), Toronto, Canada, May 14-16, 2007, LNAI 4481, Springer. (ISBN: 978-3-540-72457-5)
  109. J. T. Yao, D. W. Kim, J. P. Herbert, Supporting Online Learning with Games, Proceedings of SPIE Vol. 6570, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007, April 9-13, 2006, Orlando, Florida, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2007), 65700G-(1-11).
  110. J. Herbert, J.T. Yao, GTSOM: Game Theoretic Self-Organizing Maps, K. Chen and L.P. Wang (eds.), Trends in Neural Computation, Springer-Verlag, 2007, pp199-224.

    2006

  111. J.T. Yao, Supporting Research with Weblogs: A Study on Web-Based Research Support Systems, The 3rd International Workshop on Web-Based Support Systems, Dec 18, 2006, Hong Kong, WI-IAT 2006 Workshops Proceedings, pp161-164.
  112. J.T. Yao, S.L. Zhao, L. Fan, An Enhanced Support Vector Machine Model for Intrusion Detection, Proceedings of the International Conference on Rough Sets and Knowledge Technology (RSKT), Chongqing, China, July 24-26, 2006, LNAI 4062, pp538-543.
  113. J. T. Yao, W. N. Liu, L. Fan, Y. Y. Yao and X. D. Yang, Supporting Sustainable Communities with Web-based Information Systems, Journal of Environmental Informatics, Vol. 7, No. 2, 2006, pp84-94.
  114. J.T. Yao, (ed.) Proceedings of the second IASTED International Conference on Web Technologies, Applications, and Services (WTAS'06), Calgary, Canada, July 17-19, 2006, ACTA Press (ISBN:0-88986-575-2)
  115. J.T. Yao, W.N. Liu, The STP Model for Solving Imprecise Problems, Proceedings of IEEE Conference on Granular Computing (GrC'06), Atlanta, USA, May 10-12, 2006, pp.683-687
  116. J. T. Yao, W.N. Liu, Web-based Dynamic Delphi: a New Survey Instrument, Proceedings of SPIE No 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006, April 17-18, 2006, Orlando, Florida, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2006), pp.169-179.
  117. Y. Zhao, Y.Y. Yao, and J.T. Yao, Level construction of decision trees for classification, International Journal of Software Engineering and Knowledge Engineering (IJSEKE), Vol. 16 No. 1, pp103-126, Feb 2006.
  118. J.T. Yao, Y.Y. Yao, and Y. Zhao, Foundations of Classification, in T.Y. Lin, S. Ohsuga, C.J. Liau, and X. Hu (Eds), Foundations and Novel Approaches in Data Mining, Springer-Verlag, 2006, pp75-97.

    2005

  119. J.T. Yao, On Web-based Support Systems, Proceedings of the 2nd Indian International Conference on Artificial Intelligence, Pune, India, December 20-22, 2005, pp2589-2600.
  120. K.L. Wang, Y. Wang, and J.T. Yao, A Comparative Study on Marketing Mix Models for Digital Products, Proceedings of the First International Workshop on Internet and Network Economics (WINE'05), Hong Kong, China, December 15-17, 2005, LNCS 3828, pp660-669.
  121. J. T. Yao, Knowledge extracted from trained neural networks: what's next?, Medium Econometrisch Toepassingen (Medium for Econometric Applications), Vol. 13, Issue 4, pp26-31, 2005, (Republish from SPIE 5812)
  122. D. Slezak, J.T. Yao, J. Peters, W. Ziarko, and X. Hu (Eds.), Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC'05), II, Regina, Canada, Aug 31- Sept 3, 2005, LNAI 3642, Springer. (ISBN: 978-3-540-28660-8)
  123. J.T. Yao and M. Zhang, Feature Selection with Adjustable Criteria, Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC'05), I, Regina, Canada, Aug 31 - Sept 3, 2005, LNAI 3641 pp.204-213.
  124. J. Herbert, J.T. Yao, A Game-Theoretic Approach to Competitive Learning in Self-Organizing Maps, First International Conference on Natural Computation (ICNC'05), Changsha, China, August 27 - 29, LNCS 3610, 2005, pp129-138.
  125. J. T. Yao, Information Granulation and Granular Relationships, Proceedings of the IEEE Conference on Granular Computing, Beijing, China, July 25-27, 2005, pp326-329.
  126. J. Herbert, J.T. Yao, Time-Series Data Analysis with Rough Sets, 4th International Conference on Computational Intelligence in Economics and Finance (CIEF), Salt Lake City, USA July 21-26, 2005, pp908-911.
  127. J.T. Yao, Design of Web-based Support Systems, 8th International Conference on Computer Science and Informatics (CSI), Salt Lake City, USA July 21-26, 2005, pp349-352.
  128. W.N. Liu, J.T. Yao and Y.Y. Yao, Constructive Fuzzy Sets with Similarity Semantics, Proceedings of the 24th International Conference of NAFIPS, Ann Arbor, USA, June 22-25, 2005, pp591-596.
  129. J. T. Yao, S.L. Zhao, L.V. Saxton, A study on fuzzy intrusion detection, Proceedings of SPIE Vol. 5812, Data Mining, Intrusion Detection, Information Assurance, And Data Networks Security, 28 March - 1 April 2005, Orlando, Florida, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2005), pp23-30.
  130. J. T. Yao, Knowledge extracted from trained neural networks: what's next?, Proceedings of SPIE Vol. 5812, Data Mining, Intrusion Detection, Information Assurance, And Data Networks Security, 28 March - 1 April 2005, Orlando, Florida, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2005), pp151-157.

    2004

  131. J. T. Yao and M. Zhang, A Fast Tree Pattern Matching Algorithm for XML Query, Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, Beijing, China, Sept 20-24, 2004, pp235-241.
  132. Y.Y. Yao, J.T. Yao, C.J. Butz, P. Lingras and D. Jutla, Web-based Support Systems: a Report of the WIC Canada Research Centre, Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, Beijing, China, Sept 20-24, 2004, pp787-788.
  133. W.N. Liu, J.T. Yao, L. Fan, Y.Y. Yao, X.D. Yang, Web-based Support Systems for Sustainable Communities, Proceedings of the Second Workshop Web-based S upport Systems (WSS'04), Beijing, China, Sept 20, 2004, pp102-110.
  134. J. T. Yao, V.V. Raghavan, G.Y. Wang,, Proceedings of the Second Workshop Web-based Support Systems (WSS'04), Beijing, China, Sept 20, 2004.(ISBN 0-9734039-6-9)
  135. M. Zhang, J.T. Yao, A Rough Sets Based Approach to Feature Selection, Proceedings of The 23rd International Conference of NAFIPS, Banff, Canada, June 27-30, 2004, pp434-439.
  136. Y.Y. Yao, Y. Zhao, J.T. Yao, Level Construction of Decision Trees in a Partition-based Framework for Classification, Proceedings of the 16th International Conference on Software Engineering and Knowledge Engineering (SEKE'04), Banff, Alberta, Canada, June 20-24, 2004, pp199-204.
  137. W.-N. Liu, J.T. Yao, Y.Y.Yao, Rough Approximations under Lever Fuzzy Sets, Fourth International Conference on Rough Sets and Current Trends in Computing (RSCTC'04), Uppsala, Sweden, June 1-5, 2004, LNAI 3066, pp78-83.
  138. M. Zhang, J.T. Yao, XML Algebra for Data Mining, Proceedings of SPIE Vol. #5433, Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI, 12-13 April 2004, Orlando, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2004), pp209-217.
  139. Y.L. Zhao, J.T. Yao, Y.Y. Yao, Data Mining Support Systems, Proceedings of SPIE Vol. #5433, Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI, 12-13 April 2004, Orlando, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2004), pp218-227.
  140. J.T. Yao, Ecommerce adoption of insurance companies in New Zealand, Journal of Electronic Commerce Research, Vol. 5, No. 1, pp54-61, 2004.

    2003

  141. C.-W. Tao, H.T. Nguyen, J.T. Yao, and V. Kreinovich, Sensitivity Analysis of Neural Control, The Fourth International Conference on Intelligent Technologies (InTech'03), ChiangMai, Thailand , December 17-19, 2003. pp478-482.
  142. J. T. Yao, Y.Y., Yao, Web-based Information Retrieval Support Systems: building research tools for scientists in the new information age , Proceedings of the IEEE/WIC International Conference on Web Intelligence (WI'03), Halifax, Canada, Oct 13-17, 2003, pp570-573.
  143. H. Tang, Yu Wu, J.T. Yao, G.Y. Wang, Y. Y. Yao, CUPTRSS: A Web-based Research Support System, Proceedings of the Workshop on Applications, Products and Services of Web-based Support Systems (WSS03), Halifax, Canada, Oct 13, 2003, pp21-28.
  144. J. T. Yao, Y.Y. Yao, Web-based Support Systems, Proceedings of the Workshop on Applications, Products and Services of Web-based Support Systems (WSS'03), Halifax, Canada, Oct 13, 2003, pp1-5.
  145. J. T. Yao, P. Lingras, Proceedings of the Workshop on Applications, Products and Services of Web-based Support Systems (WSS'03), Halifax, Canada, Oct 13, 2003. (ISBN 0-9734039-1-8)
  146. J. T. Yao, ECommerce adoption of insurance firms in New Zealand, Proceedings of 5th International Conference On Electronic Commerce (Supp.), Pittsburgh, PA, USA, Sep 30 - Oct 3, 2003.
  147. J. T. Yao, Sensitivity Analysis for Data Mining, Proceedings of The 22nd International Conference of NAFIPS (the North American Fuzzy Information Processing Society), July 24-26, Chicago, USA, 2003, pp272-277.
  148. J. T. Yao, Knowledge Based Descriptive Neural Networks, Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, May 26-29, 2003, Chongqing, China, Lecture Notes in Computer Science 2639, pp430-436.
  149. J. T. Yao, and Y. Y. Yao, Information Granulation for Web based Information Retrieval Support Systems, Proceedings of SPIE Vol. 5098 Data Mining and Knowledge Discovery: Theory, Tools, and Technology V, 21-25 April 2003, Orlando, Florida, USA, edited by Belur V. Dasarathy, (SPIE, Bellingham, WA, 2003) pp138-146.
  150. 2002

  151. J. T. Yao and Y. Y. Yao, A granular computing approach to machine learning, Proceedings of the 1st International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'02), Singapore, November 18-22, 2002, pp732-736.
  152. J. T. Yao and Y. Y. Yao, Induction of classification rules by granular computing, Rough Sets and Current Trends in Computing, Proceedings of the Third International Conference (RSCTC 2002), Lecture Notes in Artificial Intelligence 2475, Malvern, PA, USA, October 14-16, 2002, Alpigini, J.J., Peters, J.F., Skowron, A. and Zhong, N. (Eds.), Springer, Berlin, pp331-338.
  153. Y. Y. Yao and J. T. Yao, Granular Computing as a Basis for Consistent Classification Problems, Proceedings of PAKDD 2002 Workshop on Toward the Foundation of Data Mining, Taipei, Taiwan, May 6-8, 2002. Communications of Institute of Information and Computing Machinery, Vol. 5, No.2, pp.101-106, 2002.
  154. J. T. Yao, Towards a Better Forecasting Model for Economic Indices, Proceedings of The Sixth International Conference on Computer Science and Informatics, March 8 - 14, 2002, Durham, NC, USA, pp299-303.
  155. 2000 - 2001 (Massey University, New Zealand)

  156. J. T. Yao, C. L. Tan, Guidelines for Financial Forecasting with Neural Networks, Proceedings of International Conference on Neural Information Processing, Shanghai, China, 14-18 November, 2001, pp757-761
  157. J. T. Yao, C. L. Tan, A Study on Training Criteria for Financial Time Series Forecasting, Proceedings of International Conference on Neural Information Processing, Shanghai, China, 14-18 November, 2001, pp772-777
  158. J. T. Yao, C. L. Tan, Neural Networks for Technical Forecasting of Foreign Exchange Rates, in Smith, K. A. and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania, pp191-207, 2002.
  159. J. T. Yao, C. L. Tan, A Case Study on Using Neural Networks to Perform Technical Forecasting of Forex, Neurocomputing, Vol. 34, No. 1-4, pp79-98, 2000.
  160. J. T. Yao, C. L. Tan, Time dependent Directional Profit Model for Financial Time Series Forecasting, Proceedings of The IEEE-INNS-ENNS International Joint Conference on Neural Networks, Como, Italy, 24-27 July 2000, Volume V, pp291-296.
  161. J. T. Yao, C. L. Tan, Y. L. Li, Option Prices Forecasting Using Neural Network, Omega: The International Journal of Management Science, Vol. 28, No. 4, 2000, pp455-466.

    1995 - 1999 (National University of Singapore, Singapore)

  162. J. T. Yao, C. L. Tan and H.-L. Poh, Neural Networks for Technical Analysis: a Study on KLCI, International Journal of Theoretical and Applied Finance, Vol. 2, No.2, 1999, pp221-241.
  163. J. T. Yao, N. Teng, H.-L. Poh, C. L. Tan, Forecasting and Analysis of Marketing Data Using Neural Networks, Journal of Information Science and Engineering, Vol. 14, No.4, 1998, pp523-545.
  164. H.-L. Poh, J. T. Yao, T. Jasic, Neural Networks for the Analysis and Forecasting of Advertising and Promotion Impact, International Journal of Intelligent Systems in Accounting, Finance and Management, Vol. 7, No. 4, 1998, pp253-268.
  165. J. T. Yao, Y. L. Li, C. L. Tan, Forecasting the Exchange Rates of CHF vs USD Using Neural networks , Journal of Computational Intelligence in Finance, Vol.5, No.2., 1997, pp7-13.
  166. J. T. Yao, H.-L. Poh, T. Jasic, Foreign Exchange Rates Forecasting with Neural Networks,ICONIP'96 (International Conference on Neural Information Processing), Hong Kong, Sept. 24-27, 1996, pp754-759.

  167. J. T. Yao, H.-L. Poh, Forecasting The KLSE Index Using Neural Networks, ICNN'95(1995 IEEE International Conference on Neural Networks), Perth, Western Australia, Nov 1995, Volume 2, pp1012-1017
  168. J. T. Yao, H.-L. Poh, Equity Forecasting: a Case Study on the KLSE Index, NNCM'95(3rd International Conference On Neural Networks in the Capital Markets), Oct 1995, London, England., pp341-353



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