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 …

Clustering of subsequence time series remains an open issue in time series clustering.
Subsequence time series clustering is used in different fields, such as e‐commerce, outlier …

Temporal data mining deals with the harvesting of useful information from temporal data.
New initiatives in health care and business organizations have increased the importance of …

Recording sensor data is seldom a perfect process. Failures in power, communication or
storage can leave occasional blocks of data missing, affecting not only real-time monitoring …

Data Mining (DM) is a fundamental component of the Data Science process. Over recent
years a huge library of DM algorithms has been developed to tackle a variety of problems in …

Time series data is naturally formed by repeated measurements over time and their analysis
in various science and engineering disciplines precedes the digital age. With progressing …

Mining association rules is an important technique for discovering meaningful patterns in
datasets. Temporal association rule mining can be decomposed into two phases: finding …

Music is a temporal organization of sounds, and we can therefore assume that any music
representation has a structure that reflects some conceptual principles. This structure is …

Events occur in every aspect of our lives. An unexpectedly large number of events occurring
within some certain measurement (eg within some time duration or a spatial region) is called …

针对三维水声传感器网络中数据流突发检测的多源性和异质性, 对描述突发异常的特征和属性
进行形式化定义和建模; 然后, 提出一种基于进化博弈论的突发检测算法, 通过滑动窗口大小的 …