Name
Abstract | ||
|---|---|---|
With the development and popularity of various location technologies (GPS, Wireless cellular networks and etc.), people can easily access the location information of moving objects and use a variety of location-based services. In this paper, based on the feature that the location information of moving object is consecutive, we introduce the continuity in temporal and spatial as a constraint into the Sequential Pattern Mining algorithm GSP (Generalized Sequential Patterns) [3,4], and to mine frequent trajectories, and then display them in Google maps. We evaluated our method by using a large GPS dataset in real world and verified the feasibility and effectiveness of Sequential Pattern Mining algorithm in mining the frequent trajectories of multiple moving objects. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-23971-7_19 | WISM (1) |
Keywords | Field | DocType |
various location technology,frequent trajectory,sequential pattern mining algorithm,novel frequent trajectory mining,location-based service,location information,google map,real world,generalized sequential patterns,wireless cellular network,large gps dataset | Wireless cellular networks,Data mining,Computer science,GSP Algorithm,Popularity,Global Positioning System,Sequential Pattern Mining,Trajectory | Conference |
Volume | ISSN | Citations |
6987 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junhuai Li | 1 | 39 | 16.44 |
| Jinqin Wang | 2 | 1 | 0.35 |
| Yu Lei | 3 | 101 | 17.34 |
| Jing Zhang | 4 | 84 | 10.71 |