PENDING
Please predict whether this patent is acceptable.PATENT ABSTRACT: A time-series prediction apparatus 10, which is an information processing apparatus that predicts transition of time-series data on a matter, calculates a relevance level which is an index of strength of a causal relation between a plurality of matters including a prediction target matter, based on time-series data relevant to each of the matters and on time-series data relevant to the causal relation between the matters, and predicts transition of the time-series data relevant to the matter based on the calculated relevance level. The time-series prediction apparatus 10 calculates the relevance level based on collocation frequency of terms relevant to the respective matters in the time-series data relevant to the causal relation between the matters. The time-series prediction apparatus 10 builds multiple prediction models for predicting the transition of the time-series data relevant to the prediction target matter based on time-series data relevant to a matter which is in a causal relation with the prediction target matter, and integrates prediction results of the respective prediction models while weighing each of the prediction models according to the relevance level.