【Purpose/significance】 Aiming at the problem that the existing privacy protection methods of personal information do not

consider implicit feedback data, resulting in low privacy protection effect, this paper studies the privacy protection method of personal information based on explicit and implicit feedback, effectively solves the privacy protection problem of personal information con⁃tained in the network by using explicit and implicit feedback information.【Method/process】 First, extract personal information accord⁃ing to the extraction rules and save it in the database. Then, a matrix decomposition model integrating explicit and implicit feedback data is established, and the implicit feedback matrix is decomposed using EifSVD algorithm. Combining the eigendirection with the ex⁃plicit feedback model, the model solution of matrix decomposition is realized. Finally, the privacy protection scheme is used to com⁃plete the encryption protection of the solution of the matrix decomposition model, and the objective function perturbation strategy based on the differential privacy algorithm is used to protect personal privacy information.【Result/conclusion】 The experimental re⁃sults show that the method fully considers the implicit feedback data of users, has high security and reliability, improves the perfor⁃mance of personal information privacy protection, and can ensure the security of personal information privacy data when transmitting information on the server, without affecting the network transmission performance and data query efficiency.【Innovation/limitation】However, due to the relatively single experimental case in this article, the research results still have certain limitations. In the later stage, the proposed personal information privacy protection method will be verified by combining different cases to ensure the accuracyof the proposed method.