Name
Abstract | ||
|---|---|---|
•We propose a novel trend based SAX reduction technique for time series.•The technique captures the trends in a time series based on abrupt change points.•The technique is endowed with a new distance between symbolic sequences.•The proposed distance lower bounds the Euclidean distance.•The technique has better classification results than some related techniques. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2019.04.026 | Expert Systems with Applications |
Keywords | Field | DocType |
Trend,Reduction,Time series,Symbolic sequences,Classification | Data mining,Computer science,Upper and lower bounds,Euclidean distance,Algorithm,Translation lookaside buffer,Bounding overwatch | Journal |
Volume | ISSN | Citations |
130 | 0957-4174 | 1 |
PageRank | References | Authors |
0.36 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| H. Yahyaoui | 1 | 30 | 3.32 |
| Reem Al-Daihani | 2 | 1 | 0.36 |