Abstract
The goal of this paper is to discuss the necessity of separating decision rules from domain model implementation. (1) Background: can rules help to discover hidden connections between data? We propose a separated implementation of decision rules on data about fixed assets for decision support. This will enhance search results. (2) Methods and technical workflow: We used DROOLS (Decision Rules Object Oriented System) to implement decision rules on the subject of accounting decisions on fixed assets; (3) Results: Making the model involves: the existence of a domain ontology and an ontology for the developed application; the possibility of executing specified inferences; the possibility of extracting information from a database; the possibility of simulations, predictions; the possibility of addressing fuzzy questions; and (4) Conclusions: The rules, the plans, and the business models must be implemented to allow specification of control over concepts. The editing of meta models must be directed to the user to ensure adaptation and not implemented at the level of control of the data control.
Highlights
The first approach in modeling decision-making process was the rational approach, which considered that decisional choices are available and their effects are known and evaluated in terms of utility
The biased rational approach considers that the decision-making process concerns many actors that are rational-biased
This paper presents a separated decision rules implementation from the domain model with the main purpose of establishing good practices for developing decision support systems
Summary
The first approach in modeling decision-making process was the rational approach, which considered that decisional choices are available and their effects are known and evaluated in terms of utility. Simon et al [1] stated that decisions are taken by actors that are led by the purpose of achieving a maximum benefit by having a satisfactory behavior. The scientific management of Taylor et al [2], the administrative theory of Fayol et al [3], and M. Weber’s [4] bureaucracy are good examples of rational-based systems. The biased rational approach considers that the decision-making process concerns many actors that are rational-biased. In this kind of system, obtaining information is important
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