In the cross-domain recommendation system, there are cases that some users randomly score the purchased items. Since the number of users who arbitrarily scores is relatively small, when the total number of scorings for the item purchased by the users who arbitrarily score is large, random scorings have less influence on the recommendation effect. However, when the total number of scorings for the item purchased by the users who arbitrarily score is relatively small, random scorings will produce a greater impact on the recommendation effect. To solve this problem, a cross-domain personalized recommendation method based on scoring reliability was proposed. Different thresholds were set for users according to the scoring reliability. When migrating the scores in the auxiliary domain to the target domain, if the total number of scorings for an item by a user was lower than the threshold of the user, the user's scorings of the item were not migrated to the target domain, otherwise migration was performed, thereby reducing the influence of the random scorings on the recommendation effect. The experimental results show that it is better to set the user's threshold personally for different scoring reliability than setting a uniform threshold for all users and not setting a threshold for users.