Open AccessUsefulness of Mining Methods in Knowledge Source Analysis in the Construction Industry
Author(s) -
Marcin Gajzler
Publication year - 2016
Publication title -
archives of civil engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 15
eISSN - 2300-3103
pISSN - 1230-2945
DOI - 10.1515/ace-2015-0056
Subject(s) - computer science , helpfulness , scope (computer science) , knowledge extraction , knowledge acquisition , process (computing) , selection (genetic algorithm) , data science , real estate , data mining , knowledge management , artificial intelligence , psychology , social psychology , programming language , operating system , political science , law
The mining methods are classified as the methods of data analysis and the knowledge acquisition and they are derived from the methods of “Knowledge Discovery”. Within the scope of these methods, there are two main variants associated with a form of data, i.e.: “data” and “text mining”. The author of the paper tries to find an answer to a question about helpfulness and usefulness of these methods for the purpose of knowledge acquisition in the construction industry. The very process of knowledge acquisition is essential in terms of the systems and tools operating based on knowledge. Nowadays, they are the basis for the tools which support the decision-making processes. The paper presents three cases studies. The mining methods have been applied to practical problems - the selection of an adhesive mortar coupled with alternative solutions, analysis of residential real estate locations under construction by a developer company as well as support of technical management of a building facility with a large floor area.