Name
Abstract | ||
|---|---|---|
Indoor spaces accommodate large populations of individuals. With appropriate indoor positioning, e.g., Bluetooth and RFID, in place, large amounts of trajectory data result that may serve as a foundation for a wide variety of applications, e.g., space planning, way finding, and security. This scenario calls for the indexing of indoor trajectories. Based on an appropriate notion of indoor trajectory and definitions of pertinent types of queries, the paper proposes two R-tree based structures for indexing object trajectories in symbolic indoor space. The RTR-tree represents a trajectory as a set of line segments in a space spanned by positioning readers and time. The TP2R-tree applies a data transformation that yields a representation of trajectories as points with extension along the time dimension. The paper details the structure, node organization strategies, and query processing algorithms for each index. An empirical performance study suggests that the two indexes are effective, efficient, and robust. The study also elicits the circumstances under which our proposals perform the best. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02982-0_15 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
symbolic indoor space,trajectory data result,empirical performance study,space planning,data transformation,appropriate notion,indexing object trajectory,indoor space,appropriate indoor positioning,indoor trajectory,indexation | Line segment,Data mining,Computer science,Way finding,Range query (data structures),Space planning,Search engine indexing,Multiple time dimensions,Trajectory,Bluetooth | Conference |
Volume | ISSN | Citations |
5644 | 0302-9743 | 43 |
PageRank | References | Authors |
1.42 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian S. Jensen | 1 | 10651 | 1129.45 |
| Hua Lu | 2 | 1380 | 83.74 |
| Bin Yang | 3 | 706 | 34.93 |