SSDBM
1999
IEEE
14 years 4 months ago
1999
IEEE
We address the problem of similarity search in large time series databases. We introduce a novel indexing algorithm that allows faster retrieval. The index is formed by creating b...
DAWAK
1999
Springer
14 years 4 months ago
1999
Springer
Data mining can be used to extensively automate the data analysis process. Techniques for mining interval time series, however, have not been considered. Such time series are commo...
SIGIR
1999
ACM
14 years 4 months ago
1999
ACM
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
SSDBM
2000
IEEE
14 years 4 months ago
2000
IEEE
Fast retrieval of time series in terms of their contents is important in many application domains. This paper studies database techniques supporting fast searches for time series ...
LCN
2000
IEEE
14 years 4 months ago
2000
IEEE
In this paper, variable bit rate (VBR) H.261 encoded video traffic is modeled by a nonlinear time series process. A threshold autoregressive (TAR) process is of particular interes...
IJCNN
2000
IEEE
14 years 4 months ago
2000
IEEE
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...
ICANN
2001
Springer
14 years 4 months ago
2001
Springer
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
KDD
2009
ACM
14 years 5 months ago
2009
ACM
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
IDA
2009
Springer
14 years 5 months ago
2009
Springer
Although k-means clustering is often applied to time series clustering, the underlying Euclidean distance measure is very restrictive in comparison to the human perception of time ...
ICANN
2009
Springer
14 years 5 months ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...