Abstract
AbstractAutomated compliance checking (ACC) of building designs requires automated extraction of information from building information models (BIMs). However, current industry foundation classes (IFC)-based BIMs provide limited support for ACC, because they lack the necessary information that is needed to perform compliance checking (CC). In this paper, the authors propose a new method for extending the IFC schema to incorporate CC-related information, in an objective and semiautomated manner. The method utilizes semantic natural language processing techniques and machine learning techniques to extract concepts from documents that are related to CC (e.g., building codes) and match the extracted concepts to concepts in the IFC class hierarchy. The proposed method includes a set of methods/algorithms that are combined into one computational platform: (1) a method for concept extraction that utilizes pattern-matching-based rules to extract regulatory concepts from CC-related regulatory documents; (2) a metho...
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