The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …

The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …

The recent explosion in the adoption of search engines and new media such as blogs and
Twitter have facilitated faster propagation of news and rumors. How quickly does a piece of …

Time series shapelets are small, local patterns in a time series that are highly predictive of a
class and are thus very useful features for building classifiers and for certain visualization …

From basic data mining concepts to state-of-the-art advances, this book covers the theory of
the subject as well as its application in a variety of fields. It discusses the incorporation of …

In this paper, we introduce SPIRIT (Streaming Pattern dIscoveRy in multIple Timeseries).
Given n numerical data streams, all of whose values we observe at each time tick t, SPIRIT …

How do we find patterns in author-keyword associations, evolving over time? Or in data
cubes (tensors), with product-branchcustomer sales information? And more generally, how …

Given a large collection of co-evolving multiple time-series, which contains an unknown
number of patterns of different durations, how can we efficiently and effectively find typical …

The goal of this paper is to monitor numerical streams, and to find subsequences that are
similar to a given query sequence, under the DTW (dynamic time war**) distance …

This book presents state-of-the-art of research results related to the science, technology, and
engineering of cyber-physical systems (CPS), including system architecture, development …