The recommendation algorithm of "Double Happiness" is based on the principle of big data and artificial intelligence technology. Specifically, the recommendation algorithm makes use of the following principles to match and recommend: user profile analysis: Joy Luck Media creates user profiles by collecting and analyzing users' personal information, hobbies, marriage preferences and other data. The recommendation algorithm will search for potential objects matching the user profile according to the characteristics and needs of the user profile. Similarity calculation: the recommendation algorithm will calculate the similarity between users according to their characteristics and preferences. By comparing the similarity between different users, the algorithm can find more matching potential pairs. Collaborative filtering: The recommendation algorithm also uses the principle of collaborative filtering. It analyzes the user's behavior and preferences, finds similar user groups, and recommends objects that these users like to other users. Feedback cycle: the recommendation algorithm will continuously optimize and adjust the recommendation results according to the user's feedback. User preferences and satisfaction feedback will be incorporated into the algorithm training and improvement process to provide more accurate and personalized recommendations.
