Name
Abstract | ||
|---|---|---|
Lower-bound functions are crucial for indexing time-series data under dynamic time warping (DTW) distance. In this paper, we propose a unified framework to explain the existing lower-bound functions. Based on the framework, we further propose a group of lower-bound functions for DTW and investigate their performances through extensive experiments. Experimental results show that the new lower-bound functions are better than the existing one in most cases. An index structure based on the new lower-bound functions is also implemented. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.ins.2011.04.048 | Information Sciences |
Keywords | Field | DocType |
indexation,time series data,time series,dynamic time warping,lower bound,similarity search,spatial index | Data mining,Dynamic time warping,Computer science,Upper and lower bounds,Search engine indexing,Database | Journal |
Volume | Issue | ISSN |
181 | 19 | null |
ISBN | Citations | PageRank |
1-4244-0803-2 | 5 | 0.54 |
References | Authors | |
32 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mi Zhou | 1 | 19 | 1.42 |
| Man Hon Wong | 2 | 814 | 233.13 |