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Aggregating and Weighting Expert Knowledge in Group Decision Making

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 93))

Abstract

In this paper, we proposed a methodology based on group decision making for aggregating and weighting expert knowledge or opinions and identifying the final agreement for a group of experts. We use a case study on causes of Alzheimer’s Disease (AD) for an illustration of the procedural steps in the proposed methodology. We begin by mapping nine most commonly discussed possible causes or risk factors of Alzheimer’s disease that we obtain from the reports into the alternatives. Then, we asked medical professionals or experts to sort the alternatives by means of a fixed set of linguistic categories; each one has associated with a numerical score. We average the scores obtained by each alternative and we consider the associated preference. A method of weighting individual expert opinions is applied in order to arrange the sequence of alternatives in each step of the decision making procedure. We calculate the collective scores after we weight the opinions of the experts with the overall contributions to agreement. The sequential decision procedure is repeated until it determines a final subset of experts where all of them positively contribute to the agreement for group decision making.

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Jongsawat, N., Premchaiswadi, W. (2010). Aggregating and Weighting Expert Knowledge in Group Decision Making. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_19

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  • DOI: https://doi.org/10.1007/978-3-642-14831-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14830-9

  • Online ISBN: 978-3-642-14831-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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