In the architecture engineering and construction (AEC) industry a great number of standards, guidelines and codes play a decisive role in guaranteeing that the designed and constructed buildings meet all the stability, reliability and usability requirements. The process of checking the building designs regarding the AEC standards, guidelines and codes is manual and currently tedious for most of the time, which aroused researchers ambition of automating this process. This lead to the field of Automated Code Compliance Checking (ACCC), where the rules in AEC codes will be translated into machine-readable language and digital building models could be checked accord-ing to those translated rules. Many approaches to Automated Code Compliance Checking focus on Natural Language Processing (NPL), which describes a way for computers to analyze, understand, and derive meaning from human language. These are characterized by a high error rate, low cover rate and limited to only relatively sim-ple rules. Therefore, in this thesis Text Mining, a sub-discipline of Data Mining, is in-troduced into ACCC to identify text structures and to process information. Text Mining specifically relates to the evaluation of large amounts of unstructured, textual information. Codes and guidelines represent such a large amount of textual information and therefore it is appropriate to apply this methodology. The thesis examines to what extent the core information can be extracted in different codes by different methods and parameters in text mining.     «

In the architecture engineering and construction (AEC) industry a great number of standards, guidelines and codes play a decisive role in guaranteeing that the designed and constructed buildings meet all the stability, reliability and usability requirements. The process of checking the building designs regarding the AEC standards, guidelines and codes is manual and currently tedious for most of the time, which aroused researchers ambition of automating this process. This lead to the field of Aut...     »