About this paper

Appears in:
Pages: 3739-3745
Publication year: 2018
ISBN: 978-84-09-05948-5
ISSN: 2340-1095
doi: 10.21125/iceri.2018.1831

Conference name: 11th annual International Conference of Education, Research and Innovation
Dates: 12-14 November, 2018
Location: Seville, Spain

DATA MINING IN CONSTRUCTION RESEARCH

J. Rosłon, H. Anysz, A. Nicał

Institute of Building Engineering, Faculty of Civil Engineering, Warsaw University of Technology (POLAND)
Data mining is the process of discovering patterns in large data sets involving different methods at the intersection of machine learning, statistics, and database systems. This interdisciplinary subfield of computer science is currently being used in most of the industries and helps to discover different (sometimes unexpected) dependencies.

Over the recent years, the construction industry has been adapting the information technology (IT) in terms of computer design, construction documentation, maintenance, cost estimates, schedules (for example through BIM – Building Information Modelling), sales, procurement, etc. Gathered information about buildings, contracts, facilities, their use and maintenance generates a solid platform for the use of data mining.

Using data mining methods in construction can improve the management and maintenance processes. Stakeholders like: architects, building managers, contractors, engineers, and owners can obtain important information from the databases using one of the numerous tools mentioned in the article (for example CART, MARS, ANN, SVM).

Data mining can also allow for discovering of previously unknown dependencies in processes like construction training or decision-making.
The article is a review of the data mining and machine learning methods used in construction. It presents current applications and academic research projects.

Authors describe the phenomena, identify relevant publications, asses them, summarize and interpret significant findings. As a result, missing areas, trends and research opportunities are outlined.
@InProceedings{ROSLON2018DAT,
author = {Rosłon, J. and Anysz, H. and Nicał, A.},
title = {DATA MINING IN CONSTRUCTION RESEARCH},
series = {11th annual International Conference of Education, Research and Innovation},
booktitle = {ICERI2018 Proceedings},
isbn = {978-84-09-05948-5},
issn = {2340-1095},
doi = {10.21125/iceri.2018.1831},
url = {http://dx.doi.org/10.21125/iceri.2018.1831},
publisher = {IATED},
location = {Seville, Spain},
month = {12-14 November, 2018},
year = {2018},
pages = {3739-3745}}
TY - CONF
AU - J. Rosłon AU - H. Anysz AU - A. Nicał
TI - DATA MINING IN CONSTRUCTION RESEARCH
SN - 978-84-09-05948-5/2340-1095
DO - 10.21125/iceri.2018.1831
PY - 2018
Y1 - 12-14 November, 2018
CI - Seville, Spain
JO - 11th annual International Conference of Education, Research and Innovation
JA - ICERI2018 Proceedings
SP - 3739
EP - 3745
ER -
J. Rosłon, H. Anysz, A. Nicał (2018) DATA MINING IN CONSTRUCTION RESEARCH, ICERI2018 Proceedings, pp. 3739-3745.
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