Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

Mining information and knowledge from large databases has been recognized by many
researchers as a key research topic in database systems and machine learning, and by …

Fast indexing in time sequence databases for similarity searching has attracted a lot of
research recently. Most of the proposals, however, typically centered around the Euclidean …

Publisher Summary Maintaining multistream and time-delayed statistics in a continuous
online fashion is a significant challenge in data management. This chapter solves this …

Considers the use of wavelet transformations as a dimensionality reduction technique to
permit efficient similarity searching over high-dimensional time-series data. While numerous …

We address the handling of time series search based on two important distance definitions:
Euclidean distance and time war** distance. The conventional method reduces the …

Distance measures are core building blocks in time-series analysis and the subject of active
research for decades. Unfortunately, the most detailed experimental study in this area is …

Sequential pattern mining, which discovers frequent subsequences as patterns in a
sequence database, in an important data-mining problem with broad applications. Although …

We consider the problem of computing all-pair correlations in a warehouse containing a
large number (eg, tens of thousands) of time-series (or, signals). The problem arises in …

Previous research on mining sequential patterns mainly focused on discovering patterns
from point-based event data. Little effort has been put toward mining patterns from interval …