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Semiautomated Generation of Logic Rules for Tabular Information in Building Codes to Support Automated Code Compliance Checking

计算机科学 编码(集合论) 过程(计算) 信息抽取 数据挖掘 源代码 程序设计语言 数据库 情报检索 集合(抽象数据类型)
作者
Xiaorui Xue,Jin Wu,Jiansong Zhang
出处
期刊:Journal of Computing in Civil Engineering [American Society of Civil Engineers]
卷期号:36 (1) 被引量:16
标识
DOI:10.1061/(asce)cp.1943-5487.0001000
摘要

To fully automate building code compliance checking, regulatory requirements need to be automatically extracted and transformed from building codes. Existing regulatory requirement processing efforts mainly focus on building code requirements in text. A more efficient approach for processing regulatory requirements in other parts of building codes, such as tables or charts, remains to be addressed. The ability to process building code requirements in all parts and formats is necessary for an automated code compliance checking system to achieve full coverage of checkable building code requirements. To address this gap, the authors propose a semiautomated information extraction and transformation method. The proposed method can extract building code requirements in tables and convert extracted information to logic rules. Automated code compliance checking systems can utilize the logic rules. The proposed method includes two main steps: (1) tabular information extraction, and (2) rule generation. The tabular information extraction semiautomatically detects the layout of tables, extracts building code requirements from tables, and transforms extracted information to databases. The rule generation step automatically generates logic rules that can be directly executed by logic reasoners. The rule generation step also provides options for users to further refine the generated rules. The development of the tabular information extraction algorithm takes an iterative approach. An experiment was conducted to develop a tabular information extraction algorithm from a section of existing code. The primary version of the algorithm correctly processed 91.67% of tables in a second sample section. After iterative refinements, the updated tabular information extraction algorithm correctly processed all tables in this section. The rule generation algorithm correctly generated logic rules that successfully represented the applicable building code requirements for a testing building, a convenience store in Texas based on the tabular information.
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