Personalized recommendation method and system based on connection matrix

The invention belongs to the technical field of personalized recommendation, and particularly relates to a personalized recommendation method and system based on a connection matrix, and the method comprises the steps: constructing a user relation network and a commodity relation network according to user social data, commodity category data and the decibel of user-to-commodity score data; obtaining a user feature representation vector and a commodity feature representation vector in the user relation network and the commodity relation network by using a network representation learning algorithm; constructing a score prediction model, taking a user feature representation vector and a commodity feature representation vector as model input, fitting the user feature representation vector and the commodity feature representation vector through a connection matrix, taking an inner product of the three as a prediction score output by the model, and training the model by a stochastic gradient descent algorithm; and