| Title | Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities |
|---|---|
| ID_Doc | 40945 |
| Authors | Murdani, MH; Kwon, J; Choi, YH; Hong, B |
| Title | Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities |
| Year | 2018 |
| Published | Sensors, 18, 4 |
| Abstract | In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naive approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space. |
| https://www.mdpi.com/1424-8220/18/4/965/pdf?version=1521884844 |
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