Journal
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
Volume 30, Issue 2, Pages -Publisher
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)CP.1943-5487.0000346
Keywords
Project management; Construction management; Information management; Computer applications; Artificial intelligence; Documentation; Automated compliance checking; Automated information extraction; Semantic systems; Natural language processing; Automated construction management systems
Funding
- National Science Foundation [1201170]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1201170] Funding Source: National Science Foundation
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Automated regulatory compliance checking requires automated extraction of requirements from regulatory textual documents and their formalization in a computer-processable rule representation. Such information extraction (IE) is a challenging task that requires complex analysis and processing of text. Natural language processing (NLP) aims to enable computers to process natural language text in a human-like manner. This paper proposes a semantic, rule-based NLP approach for automated IE from construction regulatory documents. The proposed approach uses a set of pattern-matching-based IE rules and conflict resolution (CR) rules in IE. A variety of syntactic (syntax/grammar-related) and semantic (meaning/context-related) text features are used in the patterns of the IE and CR rules. Phrase structure grammar (PSG)-based phrasal tags and separation and sequencing of semantic information elements are proposed and used to reduce the number of needed patterns. An ontology is used to aid in the recognition of semantic text features (concepts and relations). The proposed IE algorithms were tested in extracting quantitative requirements from the 2009 International Building Code and achieved 0.969 and 0.944 precision and recall, respectively. (C) 2015 American Society of Civil Engineers.
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