Introduction to algorithms
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
VLDB '98 Proceedings of the 24rd 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
A Signature Technique for Similarity-Based Queries
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Similarity Search for Multidimensional Data Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Improved heterogeneous distance functions
Journal of Artificial Intelligence Research
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In this paper an information retrieval approach to the prediction of values of time series is suggested. Rather than trying to model the data, a pattern is searched for in a history file serving as text, and relevant occurrences are used as a basis for extrapolation. The application is to meteorological data, providing short-term predictions for certain weather features. Experiments show that the algorithm is useful for predicting the requested information, and that the predictions are far more accurate than those provided by an analytical prediction procedure based on approximations using Fourier transforms.