The invention discloses a multisource heterogeneous information-fused personalized recommendation method and system. The personalized recommendation method comprises the following steps of: acquiringuser behavior record information and storing the user behavior record information into a database, wherein the user behavior record information comprises but is not limited to various behaviors, for projects, of users, and occurrence times and places of the behaviors; carrying out linear weighting conversion on the behaviors, for the projects, of the users according to different weights, so as toobtain implicit feedback, for the projects, of the users; carrying out interaction matrix construction according to the implicit feedback, for the projects, of the users so as to obtain a user-projectinteraction matrix; and constructing a personalized recommendation model according to the user-project interaction matrix and obtaining corresponding projects recommended to the users. According to the method and system, the data dilution problem and cold start problem in collaborative filtering of data can be effectively relieved, and proper projects can be recommended to users according to specific conditions of the users, so that the friendly using experience of the users can be effectively improved.