In order to solve the problem of low recommendation precision in the traditional trip itinerary recommendation algorithm, a novel Personalized Trip Itinerary Recommendation (PTIR) algorithm based on Points Of Interest (POI) popularity and user interests was proposed. Firstly, the user's real-life travel histories were obtain by analyzing the data. Then user interests based on the time were proposed according to the stay time of each scenic spot. Finally, a calculation method of optimal trip itinerary was designed under the given travel time limits, start and end points. The experimental results of a Flickr data set show that, compared with the traditional algorithm with only considering POI popularity, the precision and recall of the proposed PTIR algorithm based on the POI popularity and user interests were greatly improved; and compared with the traditional algorithm with only considering the user interests, the precision and recall of the proposed PTIR algorithm based on the points of interest and user interests were also improved. The experimental results show that considering both the POI popularity and user interests can make the itinerary recommendation more precise.