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 …

This paper compares different indexing techniques proposed for supporting efficient access
to temporal data. The comparison is based on a collection of important performance criteria …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

We investigate techniques for analysis and retrieval of object trajectories in two or three
dimensional space. Such data usually contain a large amount of noise, that has made …

Time series stored as feature vectors can be indexed by multidimensional index trees like R-
Trees for fast retrieval. Due to the dimensionality curse problem, transformations are applied …

Fast similarity searching in large time sequence databases has typically used Euclidean
distance as a dissimilarity metric. However, for several applications, including matching of …

Much environmental and socioeconomic time-series data can be adequately modeled using
autoregressive integrated moving average (ARIMA) models. We call such time series" …

Constraints are a natural mechanism for the specification of similarity queries on time-series
data. However, to realize the expressive power of constraint programming in this context …

With the increase in the size of data sets, data mining has recently become an important
research topic and is receiving substantial interest from both academia and industry. At the …

We study a set of linear transformations on the Fourier series representation of a sequence
that can be used as the basis for similarity queries on time-series data. We show that our set …