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International Conference on Neural Information Processing

ICONIP 2012: Neural Information Processing pp 483–490Cite as

Semantic De-biased Associations (SDA) Model to Improve Ill-Structured Decision Support

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7664))

Abstract

Decision makers are subject to rely upon their biased mental models to solve ill-structured decision problems. While mental models prove to be very helpful in understanding and solving ill-structured problems, the inherent biases often lead to poor decision making. This study deals with the issue of biases by proposing Semantic De-biased Associations (SDA) model. SDA model assists user to make more informed decisions by providing de-biased, and validated domain knowledge. It employs techniques to mitigate biases from mental models; and incorporates semantics to automate the integration of mental models. The effectiveness of SDA model in solving ill-structured decision problems is illustrated in this paper through a case study.

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Author information

Authors and Affiliations

  1. Decision Systems and e-Service Intelligence Laboratory(DeSI), Centre for Quantum Computation and Intelligent Systems(QCIS), University of Technology Sydney, Australia

    Tasneem Memon, Jie Lu & Farookh Khadeer Hussain

Authors
  1. Tasneem Memon
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  2. Jie Lu
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  3. Farookh Khadeer Hussain
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Memon, T., Lu, J., Hussain, F.K. (2012). Semantic De-biased Associations (SDA) Model to Improve Ill-Structured Decision Support. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_59

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  • DOI: https://doi.org/10.1007/978-3-642-34481-7_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34480-0

  • Online ISBN: 978-3-642-34481-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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