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Recently Korean products have been getting a lot of attention in the area of electronic consumables. The abundance and ever increasing use of online reviews gives us data to use. Using online reviews we found out the trend of average yearly product category ratings of brands and also map out product features search results on google map. In this research we focus on electronic products. The implementation of this project was down in java with open source tools.

An analysis of scheduled interval between buses and demand by bus sequence number can maximize the efficiency of city bus operation, such as the adjustment of scheduled interval between buses in each route or the operation of redundant bus in response to the higher demand. We analyze a scheduled interval between buses and demand by bus sequence number according to the route in Cheongju city by utilizing multidimensional analysis of transit card transaction record data in Cheongju city. The result can be expected to qualitatively enhance operation efficiency and publicness by increasing the running efficiency of each route and the level of service for citizens.

Due to the enforcement of the Personal Information Protection Act, businesses should perform the encryption for ensuring the stability of the important data in the ERP system. This study proposes an encryption method to apply the token encryption scheme that can perform the encryption without applying the changes to the database schema, allow users to use it more easily and conveniently, and to enhance the efficiency of business operation with the SAP ERP system most commonly used in the world.

Although various analyses have been conducted for improving taxi imbalance of supply and demand, it is necessary to verify significant relation of variables deduced from analyzing process because existing researches were centered on apprehension of current condition. In this study, it was verified if time zones and weather conditions affected the number of taxi passengers on the basis of call taxi operating data for more than six months. Consequently, hypotheses were partially proved, and scientific taxi demand prediction is expected to be feasible based on the data analysis.