Name
Abstract | ||
|---|---|---|
The application of location-aware technology has increasingly accumulated a large amount of user spatiotemporal data, which gives us the opportunity to analyze users' interests and behavior patterns. This paper proposes a new method for constructing user's mobility profiles and measuring their similarity. First, a new method of using the categories of points of interest (POI) to represent the semantics of a geographical area (stay region) where a user stays for a long period of time is proposed. Second, the sequential pattern mining technique is applied to extract the user's mobility profiles. Then, the user similarity is computed based on the maximum benefit assignment problem. Finally, a comparison experiment with the existing works on the real dataset verifies the effectiveness of the proposed approach.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3290420.3290470 | Proceedings of the 4th International Conference on Communication and Information Processing |
Keywords | DocType | ISBN |
GPS, mobility profiles, semantic location, user similarity | Conference | 978-1-4503-6534-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zedong Lin | 1 | 0 | 0.68 |
| Qingtian Zeng | 2 | 242 | 43.67 |
| Hua Duan | 3 | 110 | 19.58 |
| Faming Lu | 4 | 0 | 1.35 |