The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Continually evaluating similarity-based pattern queries on a streaming time series
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Continuous queries over data streams
ACM SIGMOD Record
Efficient Similarity Search in Streaming Time Sequences
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Adaptive similarity search in streaming time series with sliding windows
Data & Knowledge Engineering
Skyline Index for Time Series Data
IEEE Transactions on Knowledge and Data Engineering
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The similarity search problem in streaming time series has become a hot research topic since such data arise in so many applications of various areas. In this problem, the fact that data streams are updated continuously as new data arrive in real time is a challenge due to expensive dimensionality reduction recomputation and index update costs. In this paper, adopting the same ideas of a delayed update policy and an incremental computation from IDC index (Incremental Discrete Fourier Transform(DFT) Computation --- Index) we propose a new approach for similarity search in streaming time series by using MP_C as dimensionality reduction method with the support of Skyline index. Our experiments show that our proposed approach for similarity search in streaming time series is more efficient than the IDC-Index in terms of pruning power, normalized CPU cost and recomputation and update time.