How to Assist Formalization of NL Regulations: Lessons from Business Rules Acquisition Experiments
Résumé
Decision systems usually rely on a set of business rules that describe the expected behavior of a system or an organization and that determine the decisions to be taken in different situations. However, rule acquisition is often the bottleneck that hinders the development of decision systems. When these rules are based on regulations written in Natural Language (NL), one solution is to derive formal business rules from the source documents. This approach also allows changing the rule base with the regulation when it is updated.
To address these problems, within the FP7 ONTORULE project, we have designed a method to formalize a base of business rules from NL regulations. We have also developed a tool that supports the work of domain experts and engineers knowledge in this process. This method of formalization involves several steps: a domain expert first extracts the relevant text fragments and rewrites them in the form of independent and autonomous rules written in controlled language; these normalized rules are then formalized for the target application by a knowledge engineer.
The talk will present the method of formalization and the tool that has been designed to assist domain experts and knowledge engineers in the exploration of textual sources and to help them interact in the formalization of business rules.