Experts in construction engineering are overwhelmed by regulatory texts. It is a heavy task to go through these texts and get an unambiguous list of requirements they contain. Moreover, with regard to the number of texts and the diversity of their writers, we cannot neglect the possibility of getting inconsistencies. Finally, these requirements are to be put close to digital representation of buildings to detect potential non-conformities. This paper examines these problems and envisions solutions to help experts. We thus envisage to automate detection and extraction of business rules in regulatory texts. Next, we propose to formalise identified requirements as SPARQL queries. These queries will serve for conformity checking on OWL-representation of buildings. Moreover, we plan to leverage these queries to detect inconsistencies in regulatory texts. © 2014 Springer International Publishing.
CITATION STYLE
Kacfah Emani, C. (2014). Automatic detection and semantic formalisation of business rules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8465 LNCS, pp. 834–844). Springer Verlag. https://doi.org/10.1007/978-3-319-07443-6_57
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