Using Data Mining Techniques to Identify Construction Claims Causes: A Case Study

Document Type

Conference Proceeding

Source of Publication

2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019

Publication Date

11-1-2019

Abstract

© 2019 IEEE. The construction industry is a complex, multifaceted sector that is characterized by a high level of claims. Several studies have aimed to examine claims in the construction industry and the associated cases. However, the existing studies in this domain have been employed conventional statistical analysis. The research described in this paper exploited data mining techniques to accurately predict and rank the causes of construction claims. Data based on the studies of Zaneldin 2006 and 2018 studies were used to predict the ability of feature selection techniques to rank the causes of claims. Various feature selection techniques were applied, and the overlap in the ranked causes was compared with those identified in the previous studies.

ISBN

9781728155326

Publisher

Institute of Electrical and Electronics Engineers Inc.

Disciplines

Computer Sciences

Keywords

Classification, Construction Claims, Data Mining, Feature Selection

Scopus ID

85078903134

Indexed in Scopus

yes

Open Access

no

Link to Full Text

Share

COinS