Name
Title | ||
|---|---|---|
Improved method for linguistic expression of time series with global trend and local features |
Abstract | ||
|---|---|---|
We have various kinds of time series such as stock prices. We understand them via their linguistic expressions in a natural language rather than conventional stochastic models. We propose an improved method to have a linguistic expression with a global trend and local features of time series. A global trend is extracted via aggregated values on the fuzzy intervals in the temporal axis and local features are specified as the positions of locally large differences between the original data and the data representing the global trend. We apply the method to the data of multimodal summarization for trend information (MuST). |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FUZZY.2009.5277088 | Jeju Island |
Keywords | Field | DocType |
fuzzy set theory,stochastic processes,time series,MuST method,aggregated value,conventional stochastic model,multimodal summarization,natural language,stock price,temporal axis,time series global trend,time series linguistic expression,time series local feature,trend information | Data mining,Time series,Expression (mathematics),Computer science,Fuzzy set,Artificial intelligence,Automatic summarization,Pattern recognition,Fuzzy logic,Stochastic process,Natural language,Stochastic modelling,Linguistics,Machine learning | Conference |
ISSN | ISBN | Citations |
1098-7584 E-ISBN : 978-1-4244-3597-5 | 978-1-4244-3597-5 | 5 |
PageRank | References | Authors |
0.49 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Motohide Umano | 1 | 183 | 28.91 |
| Mitsuhiro Okamura | 2 | 5 | 0.49 |
| Kazuhisa Seta | 3 | 5 | 0.49 |