A Practical Method for Forecasting the Future Calendar Events of Ambiguous Recurrence

We proposed a model for detecting patterns in tasks that recur irregularly. This model may be useful for predicting future tasks, but it is not clear how to extract the necessary information from the model. This paper proposes a method for forecasting future tasks by extracting statistical information from the model. First, we introduce some additional terms for expressing the statistical information. Next, we propose a new method for forecasting. Finally, we provide typical examples of recurring tasks and evaluate the method using these examples.