Fast index construction for distortion-free subsequence matching in time-series databases

In this paper we address a problem of how we can construct a multidimensional index efficiently in distortion-free subsequence matching. In the previous distortion-free subsequence matching, the index construction is a very time-consuming process since it generates a huge number of data subsequences to consider all possible positions and all possible query lengths. The real experimental results show that, the index construction time reaches several hours for a time-series with a million entries, and this means that the index construction itself is very difficult for large time-series databases. To solve this problem, we first formally analyze the index construction steps, then try to optimize the performance of each step, and finally propose two advanced algorithms of constructing a multidimensional index very fast. In particular, we present the novel concept of store-and-reuse principle, a dynamic programming technique, which stores the intermediate results and reuses them repeatedly in the next steps. Through the store-and-reuse principle, the proposed algorithms construct a multidimensional index much faster than the previous algorithm. Analytical and empirical evaluations showcase the superiority of the proposed algorithms. For a time-series of length 300,000, we reduce the index construction time from 100 minutes to 7.5 minutes, which is one or two orders of magnitude.