Human-computer interaction-based Decision Support System with Applications in Data Mining

Abstract Human–computer interaction (HCI) plays a vital role in modern intelligent systems, such as brain-machine integration, human action recognition, telemedicine, and somatosensory game. A decision support system is a combination of the information system and decision-making technology. Visual human–computer interaction decision-making is a key technique in the decision support system. This paper proposes a new visual decision-making system applicable for industrial applications, i.e. data mining topics. To assist the performance of the proposed visual decision-making system, it is designed for data mining technique applications. Furthermore, the architecture of the decision support system is analyzed based on practical data mining case study. The comprehensive experiment shows that the proposed method is effective and robust in comparison to other methods.

[1]  Nitesh V. Chawla,et al.  Data Mining for Imbalanced Datasets: An Overview , 2005, The Data Mining and Knowledge Discovery Handbook.

[2]  M.L. Manheim,et al.  An architecture for active DSS , 1988, [1988] Proceedings of the Twenty-First Annual Hawaii International Conference on System Sciences. Volume III: Decision Support and Knowledge Based Systems Track.

[3]  Carlo Giupponi,et al.  Decision Support Systems for implementing the European Water Framework Directive: The MULINO approach , 2007, Environ. Model. Softw..

[4]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[5]  Gillian R. Hayes.  The relationship of action research to human-computer interaction , 2011, TCHI.

[6]  Sang-Bing Tsai,et al.  EXAMINING HOW MANUFACTURING CORPORATIONS WIN ORDERS , 2013 .

[7]  D. Mcniel,et al.  Utility of decision support tools for assessing acute risk of violence. , 2003, Journal of consulting and clinical psychology.

[8]  S. R,et al.  Data Mining with Big Data , 2017, 2017 11th International Conference on Intelligent Systems and Control (ISCO).

[9]  Yibo Li,et al.  Multi-View Hierarchical Bidirectional Recurrent Neural Network for Depth Video Sequence Based Action Recognition , 2018, Int. J. Pattern Recognit. Artif. Intell..

[10]  Eamonn J. Keogh,et al.  Towards parameter-free data mining , 2004, KDD.

[11]  Nenad Medvidovic,et al.  Modeling software architectures in the Unified Modeling Language , 2002, TSEM.

[12]  James L. McKenney,et al.  Management decision systems : computer-based support for decision making , 1971 .

[13]  Ralph H. Sprague,et al.  A Framework for the Development of Decision Support Systems , 1993 .

[14]  Fuyuan Xiao,et al.  A Multiple-Criteria Decision-Making Method Based on D Numbers and Belief Entropy , 2019, International Journal of Fuzzy Systems.

[15]  Yong Xiang,et al.  Serious Challenges and Potential Solutions for the Industrial Internet of Things with Edge Intelligence , 2019, IEEE Network.

[16]  Pengfei Shan,et al.  Mesoscopic structure PFC∼2D model of soil rock mixture based on digital image , 2019, J. Vis. Commun. Image Represent..

[17]  Zongben Xu,et al.  New study on neural networks: the essential order of approximation , 2010, Neural Networks.

[18]  Efraim Turban,et al.  Decision Support and Business Intelligence Systems (8th Edition) , 2006 .

[19]  Thorsten O. Zander,et al.  Enhancing Human-Computer Interaction with Input from Active and Passive Brain-Computer Interfaces , 2010, Brain-Computer Interfaces.

[20]  Gerardine DeSanctis,et al.  A foundation for the study of group decision support systems , 1987 .

[21]  Samuel Berlemont,et al.  BLSTM-RNN Based 3D Gesture Classification , 2013, ICANN.

[22]  Antonis A. Argyros,et al.  Vision-based Hand Gesture Recognition for Human-Computer Interaction , 2008 .

[23]  Osman Kulak,et al.  A decision support system for fuzzy multi-attribute selection of material handling equipments , 2005, Expert Syst. Appl..

[24]  Joseph P. Bigus,et al.  Data mining with neural networks: solving business problems from application development to decision support , 1996 .

[25]  Madan G. Singh,et al.  Fuzzy analytic network process and its application to the development of decision support systems , 2003, IEEE Trans. Syst. Man Cybern. Part C.

[26]  B. Milović,et al.  Prediction and Decision Making in Health Care using Data Mining , 2012 .

[27]  Daniel A. Keim,et al.  Information Visualization and Visual Data Mining , 2002, IEEE Trans. Vis. Comput. Graph..

[28]  Lawrence B. Holder,et al.  Graph-Based Data Mining , 2000, IEEE Intell. Syst..

[29]  Milad Alemzadeh,et al.  Human-Computer Interaction: Overview on State of the Art , 2008 .

[30]  Ralph H. Sprague,et al.  Invited Article: A Framework for the Development of Decisoin Support Systems , 1980, MIS Q..

[31]  Peng Lu,et al.  Research on Application of Artificial Intelligence in Computer Network Technology , 2019, Int. J. Pattern Recognit. Artif. Intell..

[32]  Michael J. A. Berry,et al.  Mastering Data Mining: The Art and Science of Customer Relationship Management , 1999 .

[33]  Hans-Werner Gellersen,et al.  Toward Mobile Eye-Based Human-Computer Interaction , 2010, IEEE Pervasive Computing.

[34]  Cristian Hofmann,et al.  Integrating cognitive load theory and concepts of human-computer interaction , 2010, Comput. Hum. Behav..

[35]  Guo Kai.  Research on location selection model of distribution network with constrained line constraints based on genetic algorithm , 2020 .

[36]  Kai Guo,et al.  Research on location selection model of distribution network with constrained line constraints based on genetic algorithm , 2019, Neural Computing and Applications.