A SURVEY OF RECENT METHODS FOR EFFICIENT RETRIEVAL OF SIMILAR TIME SEQUENCES
Magnus Lie Hetland · Series in machine perception and artificial intelligence · 2004
Time sequences occur in many applications, ranging from science and technology to business and entertainment. In many of these applications, an analysis of time series data, and searching through large, unstructured databases based on sample sequences, is often desirable. Such similarity-based retrieval has attracted a lot of attention in recent years. Although several different approaches have appeared, most are based on the common premise of dimensionality reduction and spatial access methods. This paper gives an overview of recent research and shows how the methods fit into a general context of signature extraction.