26-05-2023 дата публикации
Номер: CN116166878A
Принадлежит:
The invention discloses a time-aware adaptive interest point recommendation method based on K-means clustering. The method comprises the following steps: 1, converting a sign-in data set into a three-dimensional scoring matrix; 2, counting the number of sign-in users, the number of accessed interest points and sign-in times in each time slot, and constructing a three-dimensional sign-in feature vector of each time slot; 3, performing K-means clustering on the time slots, and calculating the time similarity between the time slots in the same cluster; 4, calculating the user similarity at the current time by using the score information in other time slots in the same time cluster; step 5, improving a traditional user-based collaborative filtering method by using a time clustering result and time similarity in a cluster, so that the traditional user-based collaborative filtering method can adaptively generate interest point prediction scores according to current recommendation time; and 6, ...
Подробнее