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 …

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

The nearest-or near-neighbor query problems arise in a large variety of database
applications, usually in the context of similarity searching. Of late, there has been increasing …

The problem of similarity search in large time series databases has attracted much attention
recently. It is a non-trivial problem because of the inherent high dimensionality of the data …

Index structures are one of the most important tools that DBAs leverage to improve the
performance of analytics and transactional workloads. However, building several indexes …

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 …

Similarity search in large time series databases has attracted much research interest
recently. It is a difficult problem because of the typically high dimensionality of the data.. The …

We compare two different techniques for browsing through a collection of spatial objects
stored in an R-tree spatial data structure on the basis of their distances from an arbitrary …

US PATENT DOCUMENTS righted Works, monitoring a network for transmission of at least
one packet-based digital signal, extracting at least one feature from the at least one digital …

High dimensional data has always been a challenge for clustering algorithms because of
the inherent sparsity of the points. Recent research results indicate that in high dimensional …