Name
Title | ||
|---|---|---|
Suspicious Location Detection Using Trajectory Analysis & Location Backfilling - A Scalable Approach |
Abstract | ||
|---|---|---|
The increasing availability of GPS-embedded devices has introduced a new dimension in digital market especially location-based services. In practice, the location data is used to understand and predict consumer mobility behavior and trend for various purposes. In this paper, we propose two methodologies to first identify suspicious location from consumer location data and to infer location at both individual device and device to device level based on systematic solution. Using stay-point clustering and suspicious patterns we identified from extensive analysis, 20-30% of records with location were observed to be suspicious. After removing inaccurate location data, we have employed scalable heuristic approach to backfill records with location even for devices that originally had no available location. Our model showed the accuracy within 50 meters at 95th percentile across different countries, including Japan, Indonesia, India, and the United States with 10-15% increase in the number of records with location and 5-10% increase in new number of devices with location. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/BigData47090.2019.9005978 | 2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) |
Keywords | DocType | ISSN |
location, location fraud, location cleaning, backfilling, location insights | Conference | 2639-1589 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Su Bae | 1 | 0 | 0.34 |
| Aravind Ravi | 2 | 0 | 1.01 |
| Sangaralingam Kajanan | 3 | 0 | 0.34 |
| Nisha Verma | 4 | 0 | 0.68 |
| Anindya Datta | 5 | 842 | 127.21 |
| Varun Chugh | 6 | 0 | 0.34 |