Knowledge Discovery in Data in Construction Projects

Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones), the best recognized an...

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Main Authors: Szelka J., Wrona Z.
Format: Article
Language:English
Published: Sciendo 2016-06-01
Series:Archives of Civil Engineering
Subjects:
Online Access:http://www.degruyter.com/view/j/ace.2016.62.issue-2/ace-2015-0076/ace-2015-0076.xml?format=INT
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spelling doaj-07d4fd9674f34540a13bbb93121fc70a2020-11-25T00:11:59ZengSciendoArchives of Civil Engineering1230-29452016-06-0162221722810.1515/ace-2015-0076ace-2015-0076Knowledge Discovery in Data in Construction ProjectsSzelka J.0Wrona Z.1Military Academy of Land Forces in Wrocław, Czajkowskiego 109, 51-150 Wrocław, Poland, University of Zielona GóraCollege of Management “Edukacja” in Wrocław, Krakowska 56-62, 50-425 Wrocław, PolandDecision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones), the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer) and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. It has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones), allowing for the use of this knowledge in the area under consideration.http://www.degruyter.com/view/j/ace.2016.62.issue-2/ace-2015-0076/ace-2015-0076.xml?format=INTinference in engineering projectsdiscovering knowledge in datarule-based knowledge representation
collection DOAJ
language English
format Article
sources DOAJ
author Szelka J.
Wrona Z.
spellingShingle Szelka J.
Wrona Z.
Knowledge Discovery in Data in Construction Projects
Archives of Civil Engineering
inference in engineering projects
discovering knowledge in data
rule-based knowledge representation
author_facet Szelka J.
Wrona Z.
author_sort Szelka J.
title Knowledge Discovery in Data in Construction Projects
title_short Knowledge Discovery in Data in Construction Projects
title_full Knowledge Discovery in Data in Construction Projects
title_fullStr Knowledge Discovery in Data in Construction Projects
title_full_unstemmed Knowledge Discovery in Data in Construction Projects
title_sort knowledge discovery in data in construction projects
publisher Sciendo
series Archives of Civil Engineering
issn 1230-2945
publishDate 2016-06-01
description Decision-making processes, including the ones related to ill-structured problems, are of considerable significance in the area of construction projects. Computer-aided inference under such conditions requires the employment of specific methods and tools (non-algorithmic ones), the best recognized and successfully used in practice represented by expert systems. The knowledge indispensable for such systems to perform inference is most frequently acquired directly from experts (through a dialogue: a domain expert - a knowledge engineer) and from various source documents. Little is known, however, about the possibility of automating knowledge acquisition in this area and as a result, in practice it is scarcely ever used. It has to be noted that in numerous areas of management more and more attention is paid to the issue of acquiring knowledge from available data. What is known and successfully employed in the practice of aiding the decision-making is the different methods and tools. The paper attempts to select methods for knowledge discovery in data and presents possible ways of representing the acquired knowledge as well as sample tools (including programming ones), allowing for the use of this knowledge in the area under consideration.
topic inference in engineering projects
discovering knowledge in data
rule-based knowledge representation
url http://www.degruyter.com/view/j/ace.2016.62.issue-2/ace-2015-0076/ace-2015-0076.xml?format=INT
work_keys_str_mv AT szelkaj knowledgediscoveryindatainconstructionprojects
AT wronaz knowledgediscoveryindatainconstructionprojects
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