Name
Abstract | ||
|---|---|---|
Time series similarity search is an important aspect of knowledge discovery in time series, and the index of data is the key to efficiency of similarity search in time series. In order to improve the efficiency of data query, a new similarity search method is proposed for hydrological time series using Lucene function mechanism. In the initial stage, build index for data with Lucene, and then carry out wavelet transform and symbolic on data, based on the candidate set with similar symbol selected from the sequence, and utilize range search function provided by Lucene rapidly search the sub sequence from candidate set, and use DTW (dynamic time warping) algorithm to calculate the matched sequence closest to search sequence. Finally, the validity and rationality of the method are verified by using the data of a hydrological station. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CCIS.2016.7790255 | 2016 4th International Conference on Cloud Computing and Intelligence Systems (CCIS) |
Keywords | Field | DocType |
Lucene,time series,similarity,indexing,DTW | Data mining,Dynamic time warping,Pattern recognition,Computer science,Search engine indexing,Knowledge extraction,Artificial intelligence,Data query,Nearest neighbor search,Wavelet transform | Conference |
ISSN | ISBN | Citations |
2376-5933 | 978-1-5090-1257-2 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Chang | 1 | 1 | 0.78 |
| Yuansheng Lou | 2 | 1 | 3.82 |
| Lei Qiu | 3 | 44 | 10.23 |