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One of the possible ways to define then model the subjective factors is to confine the
subjective factors that will be incorporated into the model only to those that have
direct effects to decision results and have a semantic relationship with the objective
features.
Based on the discussion above, we propose a decision making model whose archi-
tecture integrates both the objective searching and subjective deliberating—the evalu-
ation process is incorporated in each separate process. The framework of the model is
shown in Fig. 1. It takes into consideration both the objective and subjective factors
during decision making process.
Objective searching and evaluation
Candidate set
Subjective deliberating and evaluation
Personalized choice set
Fig. 1.
Model architecture
We take the whole problem space S
whole
as two main spaces, one is the objective
feature space S
objective
, the other is the subjective feeling space S
subjective
. The latter is
intrigued from the former, thus can be inferred from the former by semantic mapping
using semantic differential method proposed by Osgood [10].
S
S
2.1 Objective Searching and Evaluation
At this stage, the model focuses on the objective feature factors of the problem space.
These factors are easy to formalize and evaluate, and we can use genetic algorithm or
other searching algorithms to accelerate the optimization process in decision candi-
date set finding.
2.2 Subjective Deliberating and Evaluation
During this stage, the main focus will be the subjective factors that have direct seman-
tic relationship with the objective features in a decision making process. The goal is to
