## 3 Materials and Method  
### Data Collection  
260 public infrastructure projects that were ordered by Caltrans in the last three years were collected in order to predict bid risks. Caltrans orders a large number of infrastructure projects every year and it is considered that to the effective analysis of bidding information is possible because of the amount of data that is accumulated over the years. Pre-bid clarification information including pre-bid RFI, number of issued addendum, number of bidders, owner's estimate, and average bid price of 260 projects were collected. Since the pre-bid RFI is written in the text, text mining was performed to convert the unstructured text data into structured numeric data. All collected data except for the pre-bid RFI is stored as a numeric data set, and is integrated with the converted pre-bid RFI data, which is later converted into a structured format.  
In this study, risk prediction modeling is performed by integrating unstructured text data and structured numeric data based on pre-bid clarification information to determine how uncertain risk factors in the bidding document affect project risk level. Therefore, only the projects of similar size and in similar locations were collected so that the factors, such as project size and location, which were not treated as risk factors in this study, would not affect the risk prediction results.  
Based on the fact that the bidder's bid price as compared to the owner's estimate price in pre-clarified projects is relatively lower than that in unclarified projects, as shown in Figure 2, the bidder's average bid price when compared to the owner's estimate of each project was defined as a bid risk percentage. That is, a project with a positive bid risk percentage means that the average bid prices are higher than the owner's estimate, and a project with a negative bid risk percentage means that the average bid prices are lower than the owner's estimate. In other words, a project with a high bid risk percentage can be considered as a project with high bid risks, and a project with a low bid risk percentage can be considered a project with low bid risks. The bid risk percentage, which means the average bid price compared to the owner's estimate, is calculated using Equation (1).  
\[\text{Bid Risk Percentage}=(\text{average bid price-estimate})/\text{estimate }\times 100\% \tag{1}\]  
The bid risk percentage was calculated from the owner's estimates and the average bid prices of each projects, while the risk groups of all the collected projects were determined based on the bid risk  
Figure 2: Distribution of bid price relative to estimated cost between pre-clarified projects and unclarified projects.  
percentage value. In the previous studies that suggested the optimal bid markup when considering the risks in the bidding stage of construction projects [18; 19], around 8-10% was considered reasonable to calculate the bid markup in comparison with the owner's estimate. In this study, therefore, projects with bid risk percentages exceeding 10% out of the 260 public infrastructure project data were considered to be high risk group that exceeded the appropriate level of risks. In other words, a total of 260 project data were divided into a project group with bid risk percentages that were exceeding 10% and a project group with bid risk percentages of less than 10%. To further break down risk groups, projects with bid risk percentage of 0 to 10% were allocated to a moderate risk group, while projects with less than 0% were allocated to a low risk group when considering the distribution of the collected data. The projects which an average bid cost of more than 35% when compared to the owner's estimate are excluded in this study, because it is believed such projects are incurred significant changes during the bidding process.