In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

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 …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

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 …

In the last decade there has been an explosion of interest in mining time series data.
Literally hundreds of papers have introduced new algorithms to index, classify, cluster and …

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 …

Existing studies on time series are based on two categories of distance functions. The first
category consists of the Lp-norms. They are metric distance functions but cannot support …

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

This Book Addresses All The Major And Latest Techniques Of Data Mining And Data
Warehousing. It Deals With The Latest Algorithms For Discussing Association Rules …

We consider the problem of finding rules relating patterns in a time series to other patterns in
that series, or patterns in one series to patterns in another series. A simple example is a rule …