Name
Abstract | ||
|---|---|---|
The proliferation of GPS-enabled devices has led to the development of location-based social network services such as Facebook, Twitter, and Foursquare. Users of these services not only make new friends but also post various content that contains their location. Although the existing services have continued to improve, they are still weak in handling some situations. If some users want to make a new friend, for example, they could manually search for the potential friends among the acquaintances of their friends by considering both spatial proximity and social closeness one by one. However, conventional studies have insufficiently tackled this problem yet. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ins.2017.09.049 | Information Sciences |
Keywords | Field | DocType |
Geo-social networks,Location-based services,Nearest close friends query,Spatial databases | World Wide Web,Data set,Social network,Closeness,Web query classification,Location-based service,Data objects,Cell search,Mathematics | Journal |
Volume | Issue | ISSN |
423 | C | 0020-0255 |
Citations | PageRank | References |
4 | 0.40 | 27 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changbeom Shim | 1 | 6 | 3.48 |
| Wooil Kim | 2 | 120 | 16.95 |
| Wan Heo | 3 | 4 | 0.74 |
| Sungmin Yi | 4 | 18 | 4.03 |
| Yon Dohn Chung | 5 | 666 | 48.55 |