Method and system for realizing user-related recommendation

A related recommendation and user technology, applied in data processing applications, business, instruments, etc., can solve the problems of complex interaction, inability to ensure performance, and time-consuming

Active Publication Date: 2019-09-27
THE FOURTH PARADIGM BEIJING TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0008] However, in practical applications, the interaction between the user and the object may be more complex, and the vector inner product as an interaction function may not achieve the best performance for various CF tasks, and operations other than the vector inner product (e.g., vector addition, Vector concatenation, vector outer product, etc., vector convolution) used as an interaction function may sometimes have better performance than vector inner product
[0009] On the other hand, although various vector operations as mentioned above can be u

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  • Method and system for realizing user-related recommendation
  • Method and system for realizing user-related recommendation
  • Method and system for realizing user-related recommendation

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Embodiment Construction

[0083] In order to enable those skilled in the art to better understand the present invention, the exemplary embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0084] Before starting the description of the concept of the present invention below, in order to facilitate understanding, some parameter expression forms used in this application will first be explained:

[0085] Vectors are represented by lowercase boldface, and matrices are represented by uppercase boldface.

[0086] For two vectors x and y, Represents the vector inner product of x and y, x⊙y represents the element-wise product, Represents the vector outer product, [x, y] represents the concatenation of two vectors x and y into a longer vector, x*y represents the convolution of the vectors x and y, Tr(X) represents the trace of the square matrix X, ||X|| F Denote the Frobenius norm of X, ||x|| 2 L for vector x 2 Norm, and ...

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Abstract

The invention provides a method and a system for realizing user-related recommendation. The method comprises: establishing a unified representation of an interaction function for collaborative filtering in a recommendation system; constructing an interactive function search space based on the unified representation of the interactive function; for an input evaluation matrix, determining a corresponding interaction function in the interaction function search space, the row of the evaluation matrix corresponding to a user, the column of the evaluation matrix corresponding to an object, and the matrix element in the evaluation matrix representing an evaluation of the user of the corresponding row of the matrix element on the object of the corresponding column; deriving matrix elements lost in the evaluation matrix based on collaborative filtering using the determined interaction function; and performing a user-related recommendation based on the evaluation matrix in which the lost matrix element has been restored.

Description

Technical field [0001] This application relates to user-related recommendation technology, and more specifically, to a method and system for implementing user-related recommendation using collaborative filtering. Background technique [0002] Recommendation systems are widely used in various scenarios. For example, the recommendation system can use e-commerce websites to provide customers with product information and suggestions, help users decide what products to buy, and simulate sales staff to help customers complete the purchase process. Personalized recommendation is to recommend information and commodities that users are interested in based on the user's interest characteristics and purchase behavior. Recommended objects include commodities, advertisements, news, music, etc. [0003] Collaborative filtering (CF) is a key technology of the recommendation system. Given the evaluation matrix of users and objects, CF aims to predict the missing matrix elements (that is, unknow...

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Application Information

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IPC IPC(8): G06Q30/06
CPCG06Q30/0631
Inventor 姚权铭
Owner THE FOURTH PARADIGM BEIJING TECH CO LTD
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