method for recommending a point of interest based on the true popularity of interest points and implicit trust mining

The invention discloses a method for recommending a point of interest based on the true popularity of interest points and implicit trust mining, and relates to the field of Internet technology, and the user's interest in the period is periodically changed, and the user's sign-in behavior at the point of interest is fixed. The time period is divided, and in each time period, the influence of the really popular interest points and the double implicit trust mechanism (implicit trust of similar category experts and implicit trust to potential friends) on the periodic interest point recommendationis explored. The performance of the TpCsSce-PPR model was verified on the Foursquare dataset and the Gowalla dataset. The experimental results show that the TpCsSce- PPR model is superior to the selected benchmark recommendation method in MAE and RMSE evaluation indicators. 本发明公开了基于兴趣点真流行度与隐式信任挖掘的兴趣点推荐方法，涉及互联网技术领域，针对用户兴趣在时间上呈周期变化的特性，把用户在兴趣点上的签到行为按固定的时间段进行划分，在每时间段，挖掘真正流行的兴趣点和双隐式信任机制(对相似类别专家的隐式信任和对潜在朋友的隐式信任)对周期兴趣点推荐的影响。在Fou