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Development of Automatic-Extraction Model of Poisonous Clauses in International Construction Contracts Using Rule-Based NLP

Title
Development of Automatic-Extraction Model of Poisonous Clauses in International Construction Contracts Using Rule-Based NLP
Authors
Lee, JeeHeeYi, June-SeongSon, JeongWook
Ewha Authors
이준성손정욱
SCOPUS Author ID
이준성scopus; 손정욱scopus
Issue Date
2019
Journal Title
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
ISSN
0887-3801JCR Link

1943-5487JCR Link
Citation
JOURNAL OF COMPUTING IN CIVIL ENGINEERING vol. 33, no. 3
Keywords
Natural language processing (NLP)Information extraction (IE)Rule-based NLPContract risksPoisonous clausesAutomatic-extraction model
Publisher
ASCE-AMER SOC CIVIL ENGINEERS
Indexed
SCI; SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
As construction projects have significantly increased in size and become more complicated, the number of claims and dispute cases between participating parties during the construction work have been continuously increasing. To prevent such claims and disputes, the participants need to be assured of their contractual positions and rights based on contract facts. For this reason, the process of writing and reviewing the contracts for construction work is crucial. Most international construction projects require contract management teams to review all the possible risks in the contracts during the bidding periods. However, it is very difficult to review a vast number of contracts in a short period of time. Therefore, in this study, we proposed an automatic model of contract-risk extraction based on natural language processing (NLP) that can automatically detect the poisonous clauses of the contract in order to support contract management for construction companies (contractors). In validating the performance of the automatic model developed in this study, we found that the precision and recall were both 81.8% compared with manual review. This study is meaningful since a model has been developed that can carry out a preemptive contract-risk review. (c) 2019 American Society of Civil Engineers.
DOI
10.1061/(ASCE)CP.1943-5487.0000807
Appears in Collections:
엘텍공과대학 > 건축공학전공 > Journal papers
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