A data processing system processes transaction database information to predict future demand using data regression techniques to extract trend line information from historical pattern frequency values. By extrapolating the trend line, a predicted pattern frequency value may be calculated. By applying regression techniques (such as least-squares approximation), the trend line information may be extracted and projected to predict the future pattern frequency which may be applied to calculate the expected value of a recommendation rule.