Elicitation and Aggregation of Experts’ Knowledge for Event Outcome Prediction, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor) ; Movaghar Rahim Abadi, Ali ($item.subfieldsMap.e)
Abstract
Given an event O and a set of experts E, we describe a method for finding a subset of experts S whose aggregated opinions best predict the outcome of O. Therefor, the problem can be regarded as team formation for performing a prediction task. In order to estimate competency of each team we propose measure Sum Squared Error which uses experts’ records of predictions during past k days. For simplicity, opinion pooling is selected as the method of information aggregation. we prove in case of simple averaging of opinions,finding best team is NP-hard. we suggest some rounding and heuristic algorithms for finding near optimal solutions. Simulation results show that a variation of tabu search used...
Cataloging briefElicitation and Aggregation of Experts’ Knowledge for Event Outcome Prediction, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor) ; Movaghar Rahim Abadi, Ali ($item.subfieldsMap.e)
Abstract
Given an event O and a set of experts E, we describe a method for finding a subset of experts S whose aggregated opinions best predict the outcome of O. Therefor, the problem can be regarded as team formation for performing a prediction task. In order to estimate competency of each team we propose measure Sum Squared Error which uses experts’ records of predictions during past k days. For simplicity, opinion pooling is selected as the method of information aggregation. we prove in case of simple averaging of opinions,finding best team is NP-hard. we suggest some rounding and heuristic algorithms for finding near optimal solutions. Simulation results show that a variation of tabu search used...
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