Name
Abstract | ||
|---|---|---|
Terrorism has wreaked havoc on today's society and people. The discovery of the regularity of terrorist attacks is of great significance to the global counterterrorism strategy. In this study, we improve the traditional location recommendation algorithm coupled with multi-source factors and spatial characteristics. We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors. The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested. The model trained in this study is tested with precision, recall, and F-Measure. The results show that, when the threshold is 0.4, the precision is as high as 88%, and the F-Measure is the highest. We assess the spatial risk of the terrorist attacks in Southeast Asia through experiments. It can be seen that the southernmost part of the Indochina peninsula and the Philippines are high-risk areas and that the medium-risk and high-risk areas are mainly distributed in the coastal areas. Therefore, future anti-terrorism measures should pay more attention to these areas. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/ijgi7090354 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION |
Keywords | Field | DocType |
location recommendation algorithm,risk assessment,terrorist attacks,multi-source factors,spatial clustering | Peninsula,Computer security,Terrorism,Risk assessment,Natural resource,Multi-source,Geography,Socioeconomic status | Journal |
Volume | Issue | ISSN |
7 | 9 | 2220-9964 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xun Zhang | 1 | 0 | 2.03 |
| Min Jin | 2 | 0 | 1.69 |
| Jingying Fu | 3 | 1 | 0.96 |
| Mengmeng Hao | 4 | 0 | 0.34 |
| Chongchong Yu | 5 | 2 | 1.73 |
| Xiaolan Xie | 6 | 1165 | 113.61 |