Abstract
We develop a highly efficient access method, called Delta-Top-Index, to answer top-k subsequence matching queries over a time series data set. Compared to a naive implementation, our index has a storage cost that is up to two orders of magnitude smaller, while providing answers within microseconds. We demonstrate the efficiency and effectiveness of our technique in an experimental evaluation with real-world data.