Walking 8,000 steps in a day is one of the important criteria to maintain our health. However, we often miss a chance to walk due to the difficulty to keep our motivation toward our health in a daily life. We propose an algorithm to search an appropriate daily walking pattern from the user's past walking record. The searched walking patterns are used for making a health promotion agent recommend an effective timing to walk. With this recommendation, users will not miss the timing when they can walk. In this study, we focused on designing the algorithm for searching a daily walking pattern, which satisfied both conditions, achieving 8,000 steps a day and being similar to the current user walking record. In a pilot performance study, it was revealed that the proposed algorithm can narrow down the walking pattern candidates and properly search the walking pattern similar to the current user walking record.