With the ever-increasing popularity of traveling markets, more people are willing to spend their time and enjoy life by visiting some points of interest (POI) especially for the citizens living in cities. Therefore, it is of practical and significant value for travel enterprises to recommend appropriate country POIs to target travelers. However, the massive POIs as well as their diversity place a heavy burden on the POIs recommendation decision making especially when the available historical traveler-POIs check-in data are very sparse. In view of this challenge, the authors put forward a novel cultural country POIs category recommendation method based on historical knowledge and experienced information (e.g., check-in time and POIs category, i.e., CPCR). At last, CPCR method is evaluated via experiments on WS-DREAM dataset.