KIM – a semantic platform for information extraction and retrieval
Natural Language Engineering
Reasoning about Conditions and Exceptions to Laws in Regulatory Conformance Checking
DEON '08 Proceedings of the 9th international conference on Deontic Logic in Computer Science
Anomalies in ontologies with rules
Web Semantics: Science, Services and Agents on the World Wide Web
An Environment for the Joint Management of Written Policies and Business Rules
ICTAI '10 Proceedings of the 2010 22nd IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Integrating written policies in business rule management systems
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
KnowWE: a Semantic Wiki for knowledge engineering
Applied Intelligence
Engineering intelligent systems on the knowledge formalization continuum
International Journal of Applied Mathematics and Computer Science - Semantic Knowledge Engineering
Lexicalized ontology for a business rules management platform: an automotive use case
RuleML'11 Proceedings of the 5th international conference on Rule-based modeling and computing on the semantic web
From regulatory texts to BRMS: how to guide the acquisition of business rules?
RuleML'12 Proceedings of the 6th international conference on Rules on the Web: research and applications
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Business rules (BR) can be acquired from complex texts such as laws, regulations or contracts. However knowledge extraction and formalization is a complex task that involves business experts as well as Information Technology engineers and that is error-prone. Instead of waiting until the rule base is completed or the BR decision system is put into production to detect problems, we propose to detect inconsistencies and errors at an early stage, before the formalization work is completed. This paper presents the quality procedures that can be implemented in the process of BR acquisition from NL regulations. We show that the documented business rule models under construction are useful to detect potential anomalies at a semi-formal level of the BR base, where the rules exploit a formal vocabulary but are simply structured into premises and conclusions. Even at the prior and textual level, these documented models give the business experts a global and structured view over the NL regulation, which helps the formalization process.