## 3 Data Collection and Pre-Processing for ARM  
The data used for ARM between the design change items indicate the design changes for a new apartment housing project conducted by a major public client. The original raw data are shown in Table 1. The data consist of 35,194 design change issues that occurred in a total of 517 projects. All design changes occurred in 12 disciplines (including architecture, structure, and mechanical) and for 17 reasons, as shown in Table 1. In addition, the attribute information of design change issues consists of the contract name, contractor, construction cost, and contractor selection method. Based on the 35,194 design changes listed above, data pre-processing and purification were performed, and a total of 6323 design change items were extracted. To this end, by analyzing the raw data, items with missing attribute information such as contract name, main contract, initial contract price, completion date, discipline, reason for design change, and details were first filtered. During the secondary filtering process, duplicate items and invalid attribute information were removed. Table 2 presents the data structure used for the ARM analysis through data pre-processing. \begin{table}
\begin{tabular}{c c} \hline \hline
**Source Data Configuration** & **Explanation** \\ \hline Number of projects & 517 \\ \hline Year of project implementation & Completed within 2015-2021 \\ \hline Number of design changes & 35,194 \\ \hline Disciplines occured the design changes & Architectural, structural, mechanical, outdoor mechanical, electrical, communication, firefighting, earthwork, earthwork of district, building earthwork, landscape, and common (12 categories) \\ \hline Reason for design change & Design change, design change by head office, design change according to the request of government agencies, design errors, design improvement, site conditions, cost reduction, extension of schedule, change of finishing materials, reflecting permit requirements, project plan change, additional construction, cost saving, civil complaints, sales promotion, completion settlement, and others (17 factors) \\ \hline Attributes defining design change items & Number, contract number, contract name, main contractor, number of contractors, design cost, expected cost, initial contract price, successful bid rate, contractor selection method, start date, contract signing date, announcement date, completion date, number of contract changes, number of design changes, increased cost by contract change, final contract price, final completion date, disciplines, reason for extension, increase/decrease cost by reason for design change, reason for design change, details, etc. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Composition of original case data. As described in Table 2, the dataset consists of 6323 design change data generated from a total of 299 projects and have 9 attribute details including number, main contractor, and contractor selection methods. All design changes occurred in 11 disciplines and occurred in 28 locations or materials of apartment house, including PIT floor, living room, dining room, corridor, and so on. Finally, there are a total of 10 reasons for design changes, including extension of schedule, civil complaints, sales promotion, project plan change, and so on. The individual design change data, input to the ARM analysis, consist of three attribute information, such as discovery, reason for design change, and location/materials, among the data organized in Table 2. Derived results of the association rules are expressed in the form of {discipline, reason for design change, location/materials} => {discipline, reason for design change, location/materials} and have the meaning of \"if\" => \"then\". In this rule, the left part is expressed as LHS, and the right part is expressed as RHS.