Method and device to determine rating matrix based on convolutional neural network

• Main Authors: CAI NIAN, LIU GUANGCONG
• Format: Patent
• Language: Chinese; English
• Published: 29.05.2018
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

An embodiment of the invention discloses a method and device to determine a rating matrix based on a convolutional neural network. The method comprises: using a pre-trained convolutional neural network to process acquired document information, and determining a target characteristic vector; establishing an initial rating matrix according users' rating information for a commodity, wherein blank items where users do not make rating may occur in the initial rating matrix; processing the initial rating matrix according to the target characteristic vector and a matrix-decomposition-based latent semantic model, processing the initial rating matrix, and filling the blank items in the initial rating matrix to obtain a target matrix. By using the convolutional neural network, it is possible to recognize context of document information of a commodity, text information of the commodity from users can be better mined, and the influence due to data sparsity problem can be weakened. By substitutingthe target characteristic