Sorting prediction-oriented social recommendation method

A recommendation method and vector technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems affecting the accuracy of recommendation systems

Inactive Publication Date: 2018-08-31
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, this method incorporates too little information into the model, and does not consider the impact of contextual information such as item label

Method used

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  • Sorting prediction-oriented social recommendation method
  • Sorting prediction-oriented social recommendation method
  • Sorting prediction-oriented social recommendation method

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Embodiment Construction

[0058] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar meanings throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0059] figure 1 It is a schematic diagram of the overall process structure of the present invention. As shown in the figure, the present invention provides a ranking prediction-oriented social recommendation method. First, the latent features of the user are proposed through the information of the user and the item, and the latent features of the item extracted by the PL (Plackett-Luce) model and the latent features of the user extracted by the LFM are modeled; then the different role features of the trustee and trustee of the user Build a multi-dimensional trust model; ...

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Abstract

The invention discloses a sorting prediction-oriented social recommendation method. The sorting prediction precision is further improved by utilizing concealed features of a user and a project. The method comprises the steps of firstly modeling the potential features of the project and the potential features of the user extracted by using LFM through utilizing a PL model; secondly building a multidimensional trust model by utilizing the user as features of a truster and a trustee; and finally performing joint modeling to build a sorting prediction model, and performing optimization processingon the model to obtain optimal first N recommendation lists. According to the method, while social network structure information is considered, two different roles of the user serve as the truster andthe trustee to perform modeling, so that the social information is combined in recommendation, and the purpose of optimizing a recommendation result can be achieved under the condition of data sparseness.

Description

technical field [0001] The invention relates to the technical field of collaborative filtering recommendation. Specifically, it relates to a ranking prediction-oriented social recommendation method. Background technique [0002] At present, the application of personalized recommendation is divided into two categories: one is rating-oriented recommendation (recommendation is performed using the method of predicting score prediction); the other is ranking-oriented recommendation. The former pays more attention to the problem of rating prediction, assuming that the user's rating data can represent the user's preference, find the highest items in the predicted rating data and recommend them to the user; the latter focuses on the user's choice of each item In terms of possibility, the recommendation list that the user may like is predicted by ranking learning. [0003] Recommendations by learning to rank are an emerging research area. At the 2013 ACM Recommendation Conference,...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 徐光侠何李杰陶荆朝代皓张令浩唐志京吴新凯
Owner CHONGQING UNIV OF POSTS & TELECOMM
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