Incremental learning optimization on knowledge discovery in dynamic business intelligent systems
暂无分享,去创建一个
Da Ruan | Dun Liu | Tianrui Li | Junbo Zhang | Tianrui Li | D. Ruan | Dun Liu | Junbo Zhang
[1] Zdzisław Pawlak,et al. Algorithm for inductive learning , 1986 .
[2] Da Ruan,et al. E-Service Intelligence , 2007 .
[3] Wojciech Ziarko,et al. DATA‐BASED ACQUISITION AND INCREMENTAL MODIFICATION OF CLASSIFICATION RULES , 1995, Comput. Intell..
[4] Yiyu Yao,et al. Three-way decisions with probabilistic rough sets , 2010, Inf. Sci..
[5] Dun Liu,et al. AN PROBABILISTIC ROUGH SET APPROACH FOR INCREMENTAL LEARNING KNOWLEDGE ON THE CHANGE OF ATTRIBUTES , 2010 .
[6] Weibin Liu,et al. Research on the approach of dynamically maintenance of approximations in rough set theory while attribute values coarsening and refining , 2009, 2009 IEEE International Conference on Granular Computing.
[7] Yiyu Yao,et al. Integrative Levels of Granularity , 2009, Human-Centric Information Processing Through Granular Modelling.
[8] Panos M. Pardalos,et al. Data Mining and Mathematical Programming , 2008 .
[9] Zdzislaw Pawlak,et al. Rough Set Theory and its Applications to Data Analysis , 1998, Cybern. Syst..
[10] Panos M. Pardalos,et al. Encyclopedia of Optimization , 2006 .
[11] Yiyu Yao,et al. A Partition Model of Granular Computing , 2004, Trans. Rough Sets.
[12] Chenggang Bai,et al. Cost-benefit factor analysis in e-services using bayesian networks , 2009, Expert Syst. Appl..
[13] Da Ruan,et al. An Incremental Approach for Inducing Knowledge from Dynamic Information Systems , 2009, Fundam. Informaticae.
[14] Witold Pedrycz,et al. Positive approximation: An accelerator for attribute reduction in rough set theory , 2010, Artif. Intell..
[15] W. Scott Spangler,et al. The integration of business intelligence and knowledge management , 2002, IBM Syst. J..
[16] Michael C. Fu,et al. Dynamic sample budget allocation in model-based optimization , 2011, J. Glob. Optim..
[17] Tong Lingyun,et al. Incremental learning of decision rules based on rough set theory , 2002, Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527).
[18] Andrzej Bargiela,et al. Human-Centric Information Processing Through Granular Modelling , 2009, Human-Centric Information Processing Through Granular Modelling.
[19] Jie Lu,et al. Fuzzy bilevel programming with multiple objectives and cooperative multiple followers , 2010, J. Glob. Optim..
[20] Shaojie Qiao,et al. A rough set based dynamic maintenance approach for approximations in coarsening and refining attribute values , 2010, Int. J. Intell. Syst..
[21] Petra Perner,et al. Data Mining - Concepts and Techniques , 2002, Künstliche Intell..
[22] Panos M. Pardalos,et al. Handbook of Multicriteria Analysis , 2010 .
[23] Francisco Herrera,et al. Combining Numerical and Linguistic Information in Group Decision Making , 1998, Inf. Sci..
[24] Jie Lu,et al. Decision Making in Multi-Issue e-Market Auction Using Fuzzy Techniques and Negotiable Attitudes , 2008, J. Theor. Appl. Electron. Commer. Res..
[25] Jie Lu,et al. Life-event modelling framework for e-government integration , 2010, Electron. Gov. an Int. J..
[26] Yiyu Yao,et al. A Decision Theoretic Framework for Approximating Concepts , 1992, Int. J. Man Mach. Stud..
[27] Panos M. Pardalos,et al. A multicriteria approach for rating the credit risk of financial institutions , 2009, Comput. Manag. Sci..
[28] Geert Wets,et al. A rough sets based characteristic relation approach for dynamic attribute generalization in data mining , 2007, Knowl. Based Syst..
[29] Shusaku Tsumoto. Extraction of Experts' Decision Process from Clinical Databases Using Rough Set Model , 1997, PKDD.
[30] Chien-Chung Chan,et al. A Rough Set Approach to Attribute Generalization in Data Mining , 1998, Inf. Sci..
[31] Wojciech Ziarko,et al. Variable Precision Rough Set Model , 1993, J. Comput. Syst. Sci..
[32] Giovanni Fasano,et al. Dynamic analysis for the selection of parameters and initial population, in particle swarm optimization , 2010, J. Glob. Optim..
[33] Dun Liu,et al. An approach for inducing interesting incremental knowledge based on the change of attribute values , 2009, 2009 IEEE International Conference on Granular Computing.
[34] Jie Lu,et al. Decision Making in Multi-Issue e-Market Auction Using Fuzzy Attitudes , 2008 .
[35] Tianrui Li,et al. APPROACHES TO INCREMENTAL LEARNING KNOWLEDGE BASED ON THE CHANGES OF ATTRIBUTES' VALUES , 2009 .
[36] Shusaku Tsumoto,et al. Accuracy and Coverage in Rough Set Rule Induction , 2002, Rough Sets and Current Trends in Computing.
[37] Chenggang Bai,et al. E-Service Cost Benefit Evaluation and Analysis , 2007, E-Service Intelligence.
[38] Roman Slowinski,et al. Incremental Induction of Decision Rules from Dominance-based Rough Approximations , 2003, RSKD.
[39] Guoyin Wang,et al. RRIA: A Rough Set and Rule Tree Based Incremental Knowledge Acquisition Algorithm , 2003, Fundam. Informaticae.
[40] Guoyin Wang,et al. Incremental Attribute Reduction Based on Elementary Sets , 2005, RSFDGrC.