Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval

This paper proposes a case-based reasoning (CBR) approach to construction hazard identification that facilitates systematic feedback of past knowledge in the form of incident cases and hazard identification. This paper focuses on two of the key components of the CBR approach: (1) a detailed knowledg...

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Main Authors: Goh, Yang Miang, Chua, D.
Format: Journal Article
Published: American Society of Civil Engineers (ASCE) 2009
Online Access:http://hdl.handle.net/20.500.11937/32542
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author Goh, Yang Miang
Chua, D.
author_facet Goh, Yang Miang
Chua, D.
author_sort Goh, Yang Miang
building Curtin Institutional Repository
collection Online Access
description This paper proposes a case-based reasoning (CBR) approach to construction hazard identification that facilitates systematic feedback of past knowledge in the form of incident cases and hazard identification. This paper focuses on two of the key components of the CBR approach: (1) a detailed knowledge representation scheme, developed based on the modified loss causation model, to codify incident cases and past hazard identification and (2) an intelligent retrieval mechanism that can automatically retrieve relevant past cases. The detailed knowledge representation scheme presented herein is designed to model both incident cases and hazard identification so that both types of knowledge repository can be retrieved simultaneously and adapted for use. The scheme also includes a linguistic structure used to facilitate indexing of cases. The retrieval mechanism is based on the concept of similarity scoring. In this paper, a novel scoring technique based on semantic networks is presented. A case study is presented to demonstrate and validate the proposed approach.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T08:28:33Z
publishDate 2009
publisher American Society of Civil Engineers (ASCE)
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spelling curtin-20.500.11937-325422017-09-13T15:25:11Z Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval Goh, Yang Miang Chua, D. This paper proposes a case-based reasoning (CBR) approach to construction hazard identification that facilitates systematic feedback of past knowledge in the form of incident cases and hazard identification. This paper focuses on two of the key components of the CBR approach: (1) a detailed knowledge representation scheme, developed based on the modified loss causation model, to codify incident cases and past hazard identification and (2) an intelligent retrieval mechanism that can automatically retrieve relevant past cases. The detailed knowledge representation scheme presented herein is designed to model both incident cases and hazard identification so that both types of knowledge repository can be retrieved simultaneously and adapted for use. The scheme also includes a linguistic structure used to facilitate indexing of cases. The retrieval mechanism is based on the concept of similarity scoring. In this paper, a novel scoring technique based on semantic networks is presented. A case study is presented to demonstrate and validate the proposed approach. 2009 Journal Article http://hdl.handle.net/20.500.11937/32542 10.1061/(ASCE)CO.1943-7862.0000093 American Society of Civil Engineers (ASCE) restricted
spellingShingle Goh, Yang Miang
Chua, D.
Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title_full Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title_fullStr Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title_full_unstemmed Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title_short Case-Based Reasoning for Construction Hazard Identification: Case Representation and Retrieval
title_sort case-based reasoning for construction hazard identification: case representation and retrieval
url http://hdl.handle.net/20.500.11937/32542