Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7891
Title: Integration of data warehouse into knowledge-based system on construction management decision making
Authors: Chau, KW 
Cao, Y
Anson, M 
Zhang, J
Keywords: Construction management
Data warehouse
Decision making
Knowledge-based system
On-line analysis processing
Issue Date: 2003
Publisher: Hong Kong Institution of Engineers
Source: HKIE transactions, 2003, v. 10, no. 1, p. 8-13 How to cite?
Journal: HKIE transactions 
Abstract: During the construction management process, an important issue is to furnish construction managers with information about and insight into the existing data with a view to facilitating more efficient decision making without interrupting the daily work of an on-line transaction processing system. With the recent advances in artificial intelligence technology, the integration of data warehouse into knowledge-based system (KBS) is a feasible solution. Data warehouse technology, which has not been applied to construction management, is a new database branch. It is meaningful to experiment and gauge the full scope of its capability in this specific problem domain. This paper describes a prototype integrated KBS, which has been developed using a commercially available microcomputer-based expert system shell VISUAL RULE STUDIO, on construction management decision making. VISUAL RULE STUDIO acts as an ActiveX Designer under the Microsoft Visual Basic programming environment, with hybrid knowledge representation approach under object-oriented design environment. The coupling enables the right data to be tracked down and furnishes the necessary information in a direct, rapid and meaningful way. Through custom-built interactive graphical user interfaces, construction managers can view data from various perspectives with significantly reduced response time to queries, thus rendering more efficient decision making. Illustrative sample sessions using the system are also presented.
URI: http://hdl.handle.net/10397/7891
ISSN: 1023-697X
EISSN: 2326-3733
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