Publications of Decision-Theoretic Rough Set Model

Compiled by Dr. Huaxiong Li

 

[1]     Ayad R. A., Liu J. Supporting E-learning system with modified Bayesian rough set model. Proceedings of the 6th International Symposium on Neural Networks, 2009: 192-200.

[2]     Azam N., Yao J. T. Multiple criteria decision analysis with game-theoretic rough sets. Proceedings of the 8th International RSCTC conference, 2012.

[3]     Chan A., Gilon D., Manor O., Paltiel O. Probabilistic reasoning and clinical decision-making: Do doctors overestimate diagnostic probabilities? QJM: An International Journal of Medicine, 2003, 96: 763-769.

[4]     Deng X. F., Yao, Y. Y., An information-theoretic interpretation of thresholds in probabilistic rough sets. Proceedings of the 8th international RSCTC conference, 2012.

[5]     Greco S., Matarazzo B., Slowinski R. Rough membership and bayesian confirmation measures for parameterized rough sets. Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 2005, Lecture Notes in Artificial Intelligence 3641.Berlin: Springer, 2005: 314-324.

[6]     Greco S., Slowinski R., Yao Y. Y. Bayesian decision theory for dominance-based rough set approach. Proceedings of 2nd International Conference on Rough Sets and Knowledge Technology, RSKT'07, 2007: 134-141.

[7]     Herbert J. P., Yao J. T. Analysis of data-driven parameters in game-theoretic rough sets. Proceedings of 6th International Conferences on Rought Set and Knowledge Technology, Banff, Canada, 2011: 444-453.

[8]     Herbert J. P., Yao J. T. Criteria for choosing a rough set model. Computers and Mathematics with Applications, 2009, 57(6): 908-918.

[9]     Herbert J. P., Yao J. T. Game-theoretic risk analysis in decision-theoretic rough sets. Proceedings of the 3rd International Conference on Rough Sets and Knowledge Technology 2008, Lecture Notes in Artificial Intelligence 5009. Berlin: Springer, 2008: 132-139.

[10]   Herbert J. P., Yao J. T. Game-theoretic rough sets. Fundamenta Informaticae, 2011, 108(3-4): 267-286.

[11]   Herbert J. P., Yao J. T. Learning optimal parameters in decision-theoretic rough sets. Proceedings of 4th Rough Sets and Knowledge Technology, Gold Coast, Australia, 2009: 610-617.

[12]   Jia X. Y., Li W. W., Shang L., Chen J. J. An optimization viewpoint on decision-theoretic rough set model. Proceedings of 6th International Conferences on Rought Set and Knowledge Technology, Banff, Canada, 2011: 454-462.

[13]   Jia X. Y., Zhang K., Shang L. Three-way decisions solution to filter spam email: An empirical study. Proceedings of the 8th international RSCTC conference, 2012.

[14]   Li H. X., Zhou X. Z. Risk decision making based on decision-theoretic rough set: A multi-view decision model. International Journal of Computational Intelligence Systems,2011, 4(1):1-11.

[15]   Li H. X., Zhou X. Z., Zhao J. B., Huang B. Cost-sensitive classification based on decision-theoretic rough set model. Proceedings of 7th International Conference on Rough Sets and Knowledge Technology, Chengdu, China, 2012: 379-388.

[16]   Li H. X., Zhou X. Z., Zhao J. B., Liu D. Attribute reduction in decision-theoretic rough set model: a further investigation. Proceedings of the 6th International Conference on Rough Sets and Knowledge Technology, RSKT'11, 2011: 466-475.

[17]   Li W., Miao D. Q., Wang W. L., Zhang N. Hierarchical rough decision theoretic framework for text classification. International Conferences on Cognitive Informatics, Beijing, China, 2010: 484-489.

[18]   Li Y., Zhang C., Swan J. R. An information filtering model on the web and its application in job agent. Knowledge-Based Systems, 2000, 13: 285-296.

[19]   Li Y., Zhang C., Swan J. R. Rough set based model in information retrieval and filtering. Proceeding of the 5th International Conference on Information Systems Analysis and Synthesis, ISAS'99, 1999: 398-403.

[20]   Lingras P., Chen M., Miao D. Q. Rough cluster quality index based on decision theory. IEEE Transactions on Knowledge and Data Engineering, 2009, 21 (7): 1014-1026.

[21]   Lingras P., Chen M., Miao D. Q. Rough multi-category decision theoretic framework. Proceedings of 3rd International Conference on Rough Sets and Knowledge Technology, Chengdu, China, 2008: 676-683.

[22]   Lingras P., Chen M., Miao D. Q. Semi-supervised rough cost/benefit decisions. Fundamenta Informaticae, 2009, 94 (2): 233-244.

[23]   Liu D., Li H. X., Zhou X. Z. Two decades'research on decision-theoretic rough sets. Proceedings of 9th IEEE International Conference on Cognitive Informatics, 2010: 968-973.

[24]   Liu D., Li T. R., Hu P., Li H. X. Multiple-category classification with decision-theoretic rough sets. 5th International Conferences on Rought Set and Knowledge Technology, Beijing, China, 2010: 703-710.

[25]   Liu D., Li T. R., Liang D. C. A new discriminant analysis approach under decision-theoretic rough sets. Proceedings of 6th International Conferences on Rought Set and Knowledge Technology, Banff, Canada, 2011: 473-482.

[26]   Liu D., Li T. R., Liang D. C. Decision-theoretic rough sets with probabilistic distribution. Proceedings of the 8th international RSCTC conference, 2012.

[27]   Liu D., Li T. R., Ruan D. Probabilistic model criteria with decision-theoretic rough sets. Information Sciences, 2011, 181, 3709-3722.

[28]   Liu D., Yao Y. Y., Li T. R. Three-way investment decisions with decision-theoretic rough sets. International Journal of Computational Intelligence Systems, International Journal of Computational Intelligence Systems,2011, 4(1): 66-74.

[29]   Liu J. B., Min F., Liao S. J., Zhu W. Minimal test cost feature selection with positive region constraint. Proceedings of the 8th international RSCTC conference, 2012.

[30]   Ma W. M., Sun B. Z. On relationship between probabilistic rough set and Bayesian risk decision over two universes. International Journal of General Systems, 2012, 41: 225~245.

[31]   Ma X. A., Wang G. Y., Yu H. Multiple-category attribute reduct using decision-theoretic rough set model. Proceedings of the 8th international RSCTC conference, 2012.

[32]   Slezak D. Rough sets and bayes factor. Transactions on Rough Sets III, Lecture Notes in Computer Science 3400.Berlin: Springer, 2005: 202-229.

[33]   Slezak D., Ziarko W. Attribute reduction in the Bayesian version of variable precision rough set model. Electronic Notes in Theoretical Computer Science, 2003, 82: 263-273.

[34]   Yang X. P., Song H. G., Li T. J. Decision making in incomplete information system based on decision-theoretic rough sets. Proceedings of 6th International Conferences on Rought Set and Knowledge Technology, Banff, Canada, 2011: 495-503.

[35]   Yang X. P., Yao J. T. A multi-agent decision-theoretic rough set model. Proceedings of 5th International Conferences on Rought Set and Knowledge Technology, Beijing, China, 2010: 711-718.

[36]   Yang X. P., Yao J. T. Modelling multi-agent three-way decisions with decision theoretic rough sets. Fundamenta Informaticae, 2012, 115: 157~171.

[37]   Yao J. T., Herbert J. P. A game-theoretic perspective on rough set analysis. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2008, 20(3): 291-298.

[38]   Yao J. T., Herbert J. P. Web-based support systems with rough set analysis. Proceedings of International Conference on Rough Sets and Intelligent Systems Paradigms 2007, Lecture Notes in Artificial Intelligence 4585. Berlin: Springer, 2007: 360-370.

[39]   Yao J. T., Zhang M. Feature selection with adjustable criteria. Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 2005, Lecture Notes in Artificial Intelligence 3641. Berlin: Springer, 2005: 204-213.

[40]   Yao Y. Y. An outline of a theory of three-way decisions. Proceedings of the 8th international RSCTC conference, 2012.

[41]   Yao Y. Y. Decision-theoretic rough set models. Proceedings of the 2nd International Conference on Rough Sets and Knowledge Technology 2007, Lecture Notes in Computer Science 4481.Heidelberg: Springer, 2007: 1-12.

[42]   Yao Y. Y. Information granulation and approximation in a decision-theoretic model of rough sets. In: Rough-neuro Computing: a Way to Computing with Words, Springer, Berlin, 2003: 491-518.

[43]   Yao Y. Y. Probabilistic approaches to rough sets. Expert Systems, 2003, 20: 287-297.

[44]   Yao Y. Y. Probabilistic rough set approximations. International Journal of Approximate Reasoning, 2008, 49(2): 255-271.

[45]   Yao Y. Y. The superiority of three-way decisions in probabilistic rough set models. Information Sciences, 2011, 181(6): 1080-1096.

[46]   Yao Y. Y. Three-way decision: an interpretation of rules in rough set theory. Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology, RSKT'09, 2009: 642-649.

[47]   Yao Y. Y. Three-way decisions with probabilistic rough sets. Information Sciences, 2010, 180: 341-353.

[48]   Yao Y. Y. Two semantic issues in a probabilistic rough set model. Fundamenta Informaticae, 2011, 108(3-4): 249-265.

[49]   Yao Y. Y., Deng X. F. Sequential three-way decisions with probabilistic rough sets. Proceedings of the 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing, 2011.

[50]   Yao Y. Y., Wong S. K. M. A decision theoretic framework for approximating concepts. International Journal of Man-machine Studies, 1992, 37(6): 793-809.

[51]   Yao Y. Y., Wong S. K. M., Lingras P. A decision-theoretic rough set model. Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems 1990: 17-25.

[52]   Yao Y. Y., Zhao Y. Attribute reduction in decision theoretic rough set models. Information Sciences, 2008, 178: 3356-3373.

[53]   Yao Y. Y., Zhou B. Naive Bayesian Rough Sets, Proceedings of 5th International Conferences on Rought Set and Knowledge Technology, Beijing, China, 2010: 719-726.

[54]   Yu H., Chu S. S., Yang D. C. A semiautonomous clustering algorithm based on decision-theoretic rough set theory, International Conferences on Cognitive Informatics, Beijing, China, 2010: 477-483.

[55]   Yu H., Chu S. S., Yang D. C. Autonomous knowledge-oriented clustering using decision-theoretic rough set theory, 5th International Conferences on Rought Set and Knowledge Technology, Beijing, China, 2010: 687-694.

[56]   Yu H., Liu Z. G., Wang G. Y. Automatically determining the number of clusters using decision-theoretic rough set. Proceedings of 6th International Conference on Rough Sets and Knowledge Technology, RSKT'11, 2011: 504-513.

[57]   Yu H., Wang Y. Three-way decisions method for overlapping clustering. Proceedings of the 8th international RSCTC conference, 2012.

[58]   Zhao Y., Wong S. K. M., Yao Y. Y. A note on attribute reduction in the decision theoretic rough set model. Proceedings of RSCTC2008, Springer-Verlag Berlin Heidelberg, 2008, LNAI 5306: 61-70.

[59]   Zhou B. A new formulation of multi-category decision-theoretic rough sets. Proceedings of 6th International Conference on Rough Sets and Knowledge Technology, RSKT'11, 2011: 514-522.

[60]   Zhou B., Yao Y. Y., Luo J. A three-way decision approach to email spam filtering. Proceeding of the 23rd Canadian Conference on Artificial Intelligence 2010, Lecture Notes in Artificial Intelligence 6085. Berlin: Springer, 2010: 28-39.

[61]   Zhou X. Z., Li H. X. A multi-view decision model based on decision-theoretic rough set. Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology, 2009: 650-657.

[62]   胡卉颖, 罗锦坤, 刘阿宁. 三枝决策粗糙集模型属性约简研究. 软件导刊, 2012, 11: 20~22.

[63]   贾修一, 李伟湋, 商琳, 陈家骏. 一种自适应求三枝决策中决策阈值的算法. 电子学报, 2011, 39: 2520~2525.

[64]   贾修一, 商琳, 陈家骏. 基于三值决策的属性约简. 中国人工智能进展2009, 北京邮电大学出版社, 2009, 193-198.

[65]   贾修一, 商琳, 陈家骏. 决策风险最小化属性约简. 计算机科学与探索, 2011, 5(2): 155-160.

[66]   贾修一, 商琳. 一种求三支决策阈值的模拟退火算法, 2012, 手稿.

[67]   贾修一,商琳,周献中,梁吉业,苗夺谦,王国胤,李天瑞,张燕平. 三支决策理论与应用. 南京:南京大学出版社, 2012.

[68]   李华雄, 刘盾, 周献中. 决策粗糙集模型研究综述. 重庆邮电大学学报(自然科学版), 2010, 22(5): 624-630.

[69]   李华雄, 周献中, 赵佳宝. 决策粗糙集的正域约简// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[70]   李华雄, 周献中. 决策粗糙集理论方法研究综述// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[71]   李华雄,周献中,李天瑞,王国胤,苗夺谦,姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社,2011.

[72]   刘盾, 李天瑞. 三枝决策粗糙集// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[73]   刘盾, 姚一豫, 李天瑞. 三枝决策粗糙集. 计算机科学, 2011, 38(1): 245-250.

[74]   苗夺谦, 李文, 周杰. 基于决策粗糙集模型的文本分类研究// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[75]   杨晓平, 姚静涛. 多用户决策粗糙集模型// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[76]   于洪, 储双双. 一种基于决策粗糙集的自动聚类方法. 计算机科学, 2011, 38: 221~224.

[77]   于洪, 王国胤. 基于决策粗糙集的自动聚类方法// 李华雄, 周献中, 李天瑞, 王国胤, 苗夺谦, 姚一豫. 决策粗糙集理论及其研究进展. 北京:科学出版社, 2011.

[78]   张文修, 吴伟志, 粱吉业, 李德玉. 粗糙集理论与方法. 北京: 科学出版社, 2001: 142-148.

[79]   赵文清,朱永利,高伟. 一个基于决策粗糙集理论的信息过滤模型. 计算机工程与应用,2007, 43(7): 185-187.