| 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 |
| DOI |
10.3390/s18040965 |
| 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. |
| Author Keywords |
proximity computation; data models; ZIP code data; smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000435574800037 |
| WoS Category |
Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation |
| Research Area |
Chemistry; Engineering; Instruments & Instrumentation |
| PDF |
https://www.mdpi.com/1424-8220/18/4/965/pdf?version=1521884844
|