Before revision:  In our research, we separate the assessments of future economic conditions into  near and distant future economic conditions using learning from positive and unlabeled data (PU learning) , which is weakly supervised learning. The dataset is composed of several periods, and we develop a PU learning algorithm for efficient training, using the dataset with the time series.
After revision:  In our research, we separate the assessments of future economic conditions into near and distant future economic conditions using learning from positive and unlabeled data (PU learning) . Because the dataset includes data from several periods, and we develop a PU learning algorithm for efficient training, using the dataset with the time series.