An algorithm for robust relative influence values elicitation (ARRIVE)

S. E. Hegazy, C. D. Buckingham

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

This paper proposes an approach to solving node weightings in a tree structure. The tree represents expertise used to quantify risks associated with mental-health problems and it is incorporated within a web-based decision support system called GRiST. The aim of the algorithm is to find the set of relative node weightings in the tree that helps GRiST simulate the clinical risk judgements given by mental-health experts. The results show that a very large number of nodes (several thousand for GRiST) can have their weights calculated from the clinical judgements associated with a few hundred cases (200 for GRiST). This greatly reduces the experts' elicitation tasks by ensuring they do not need to provide their own estimation of node weights throughout the tree. The approach has the potential for reducing elicitation load in similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

Original languageEnglish
Title of host publicationProc. - The 3rd Int. Multi-Conf. Computing in the Global Information Technology, ICCGI 2008 in Conjunction with ComP2P 2008: The 1st Int. Workshop on Computational P2P Networks: Theory and Practice
Pages91-96
Number of pages6
DOIs
Publication statusPublished - 26 Sep 2008
Event3rd International Multi-Conference on Computing in the Global Information Technology, ICCGI 2008 - Athens, United Kingdom
Duration: 27 Jul 20081 Aug 2008

Conference

Conference3rd International Multi-Conference on Computing in the Global Information Technology, ICCGI 2008
CountryUnited Kingdom
CityAthens
Period27/07/081/08/08

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