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
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 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
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
On Similarity Queries for Time-Series Data: Constraint Specification and Implementation
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Efficient moving average transform-based subsequence matching algorithms in time-series databases
Information Sciences: an International Journal
Fast Normalization-Transformed Subsequence Matching in Time-Series Databases
IEICE - Transactions on Information and Systems
A review on time series data mining
Engineering Applications of Artificial Intelligence
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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In this paper, we propose a subsequence matching algorithm that supports moving average transform of arbitrary order in time-series databases. The existing subsequence matching algorithm by Faloutsos et al. would require an index for each moving average order, which causes serious storage and CPU time overhead. In this paper, we solve the problem using index interpolation. The proposed algorithm can use only a few indexes for pre-selected moving average orders k and performs subsequence matching for arbitrary order m (≤ k). We prove that the proposed algorithm causes no false dismissal. For selectivities less than 10-2, the degradation of search performance compared with the fully-indexed case is no more than 17.2 % when two out of 128 indexes are used. The algorithm works better with smaller selectivities.