Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

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 …

Similarity-based search over time-series databases has been a hot research topic for a long
history, which is widely used in many applications, including multimedia retrieval, data …

This paper proposes a trend-oriented time series granulation method to transform a long
numerical time series into a relatively short granular time series which is consist of a group …

Clipping is the process of transforming a real valued series into a sequence of bits
representing whether each data is above or below the average. In this paper, we argue that …

Current research in indexing and mining time series data has produced many interesting
algorithms and representations. However, the algorithms and the size of data considered …

This paper is concerned with an introduction to big data which can be potentially used in
nowcasting the UK GDP and other key macroeconomic variables. We discuss various big …

An important goal of knowledge discovery is the search for patterns in data that can help
explain the underlying process that generated the data. The patterns are required to be new …

现实世界存在着大量的时态数据, 时态数据挖掘(temporal data mining, 简称TDM)
是近年来学术界关注的一个重要研究课题. 相似性发现技术关注数据的发展变化 …

This paper describes a dynamical model-based method for the localization of road vehicles
using terrain data from the vehicle's onboard sensors. Road data are encoded using linear …