The S-Tree: An Index Structure for Subsequence Matching of Spatial Objects

Abstract. We present the S-Tree, an indexing method for subsequence matching of spatial objects. The S-Tree locates subsequences within a collection of spatial sequences, i.e., sequences made up of spatial objects, such that the subsequences match a given query pattern within a specified tolerance. Our method is based on (i) the string-searching techniques that locate substrings within a string of symbols drawn from a discrete alphabet (e.g., ASCII characters) and (ii) the spatial access methods that index (unsequenced) spatial objects. Particularly, the S-Tree can be applied to solve problems such as subsequence matching of time-series data, where features of subsequences are often extracted and mapped into spatial objects. Moreover, it supports queries such as “what is the longest common pattern of the two time series?”, which previous subsequence matching algorithms find difficult to solve efficiently.