Automating Coordination Efforts for Reviewing Construction Contracts with Multilabel Text Classification

Date

2022-06-01

Author

Candas, Ali Bedii
Tokdemir, Onur Behzat

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

264
views

0
downloads

Construction projects involve multiple company departments and disciplines. The departments follow certain rules in implementing a project, also referred to as requirements in a construction contract. Current administration practices do not show which discipline or department is related to any requirement in the contracts. Thus, all departments need to review contract requirements but typically only from their perspective and with minimal communication with one another. In addition to the tendency of this manual process to error, time and money are lost in evaluating irrelevant departmental requirements. This study concentrates on one aspect of contract interpretation, coordination of the contract requirement review. Automating a classification of the contract requirements by relevant departments can increase the efficiency of contract reviews. This study proposes a robust approach to automating contract sentence classification by relevance to the company department. The approach comprises both natural language processing (NLP) and supervised machine learning techniques to train an algorithm. Training data are selected from an internationally and widely used standard form of construction contract. Precision metric results as high as 0.952 and recall metric results as high as 0.786 are acquired by support vector classifiers (SVCs). These are considered sufficient within the context of multilabel classification of construction contract sentences for construction professionals to operate without further training. The developed methodology reduces time spent on contract review, reliably and accurately predicts classification of contract sentences for departmental relevance, and also removes the dependence on expert participation in coordination efforts contract review.

Subject Keywords

Construction contracts, Contract administration, Machine learning, Metrics, Multilabel classification, Natural language processing (NLP)

URI

https://hdl.handle.net/11511/97177

Journal

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT

DOI

https://doi.org/10.1061/(asce)co.1943-7862.0002275

Collections

Department of Civil Engineering, Article

Suggestions

OpenMETU
Core

Using natural language processing for automated construction contract review during risk assessment at the bidding stage Eken, Görkem; Birgönül, Mustafa Talat; Dikmen Toker, İrem; Department of Civil Engineering (2022-12) Construction sector contains various risks, and construction projects are open to failure due to their nature and the involvement of multiple parties. Contracts are legal documents that are used to define the responsibilities of parties in a project. Risks that are taken by a party are highly related to their positions in the contracts. However, contracts are prepared by clients, and contractors generally do not have enough time to review their responsibilities before preparing their bids. Moreover, contrac...
An investigation of legal aspects of BIM in construction contracts Kaya, Fatih; Akçamete Güngör, Aslı; Birgönül, Mustafa Talat (null; 2019-04-17) Building Information Modeling (BIM) has been adopted worldwide in recent years as a novel way of working that enables efficiency in the construction industry. Lately, numerous countries made it compulsory to utilize BIM in public construction projects. Similarly, BIM became a contractual requirement in some public infrastructure and Build-Operate-Transfer (BOT) projects in Turkey. However, in order to benefit from the advantages of BIM, some legal concerns such as intellectual property, liability, legal val...
A Causal mapping approach for the analysis of construction disputes Tanrıverdi, Cenk; Dikmen Toker, İrem; Department of Civil Engineering (2019) Containing various work disciplines, numerous stakeholders, and relatively extensive procedures due to its nature, disputes are frequently encountered in construction projects. The fact that disputes can have devastating effects on success of projects in terms of both time and cost to both parties involved when not dealt with care, makes a clear understanding of how and why disputes occur in construction projects an important research topic. Previous studies on this subject has mostly yielded only exhaustiv...
Integrated Approach to Overcome Shortcomings in Current Delay Analysis Practices Birgönül, Mustafa Talat; Dikmen Toker, İrem (American Society of Civil Engineers (ASCE), 2015-04-01) Many factors, such as unforeseeable events, managerial and financial problems of contractors, insufficient technical capacity of site teams of contractors or Consultants, and so on, may lead to delays in construction projects. Proper analysis of compensability and quantum of a delay event is of prime importance. Any delay analysis application can be considered as a result of the combination of contract documents, scheduler, record-keeping mechanism at the site, communication among project participants, dela...
A lessons learned database structure for construction companies Eken, Görkem; Dikmen Toker, İrem; Birgönül, Mustafa Talat (2015-06-24) Knowledge management in project based industries is critical as in the case of construction industry. Besides being a project based industry, factors specific to construction projects also make it harder to capture knowledge. Construction projects are held in dispersed locations, by different parties involved, with variable objectives; all of which make capturing the information more difficult and knowledge management process more complex. This study presents a database structure and an information system t...

Citation Formats

A. B. Candas and O. B. Tokdemir, “Automating Coordination Efforts for Reviewing Construction Contracts with Multilabel Text Classification,” JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, vol. 148, no. 6, pp. 0–0, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/97177.