An information retrieval approach to predicting meteorological data

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.