Name
Abstract | ||
|---|---|---|
Rank order correlation has been used extensively when the data is non-parametric or when the relationship between two variables is nonlinear and monotonic. In such cases, linear correlation measures, such as the product-moment coefficient, are inadequate and fail to detect correlative relations. We present a polyhedral indexing technique for rank order correlation queries for time series data. We use an interesting geometry interpretation of rank order correlation which lends itself to indexing by spatial indexes such as R-trees. Our experimental results indicate one to two orders of magnitudes improvement over sequential scan - the only alternative solution. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1458082.1458342 | CIKM |
Keywords | Field | DocType |
magnitudes improvement,polyhedral indexing technique,correlative relation,linear correlation measure,polyhedral transformation,interesting geometry interpretation,alternative solution,rank order correlation query,time series data,rank order correlation,spatial index,indexation,dimensionality reduction | Data mining,Time series,Monotonic function,Nonlinear system,Dimensionality reduction,Ranking,Computer science,Full table scan,Algorithm,Search engine indexing,Correlation,Statistics | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Philon Nguyen | 1 | 3 | 1.73 |
| Nematollaah Shiri | 2 | 280 | 28.31 |