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Item recommendation method and system based on collaborative filtering model

A technology of collaborative filtering and recommendation methods, applied in neural learning methods, biological neural network models, instruments, etc., to achieve the effect of improving execution efficiency

Pending Publication Date: 2021-11-19
THE FOURTH PARADIGM BEIJING TECH CO LTD
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  • Summary
  • Abstract
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Problems solved by technology

[0005] Existing collaborative filtering models are usually designed by experts, and the designed collaborative filtering model needs to be continuously adjusted during use (for example, the initial collaborative filtering model is adjusted according to the task). Therefore, how to automatically select an effective collaborative filtering model for item Referrals have become a very important issue

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  • Item recommendation method and system based on collaborative filtering model
  • Item recommendation method and system based on collaborative filtering model
  • Item recommendation method and system based on collaborative filtering model

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Embodiment Construction

[0033] In order that those skilled in the art better understand the present invention, the following exemplary embodiments of the present invention are described in further detail in conjunction with accompanying drawings and specific embodiments.

[0034] Before beginning the following description of the invention concept, for ease of understanding, mathematical problem described herein requires cooperative filtering corresponding to the task according to an exemplary embodiment of the present disclosure, the mathematical expression of the problems are as follows:

[0035] fly * = Arg min f∈F M (f (P * ), S val )

[0036] s.tP * = Arg min M (f (P), S train )

[0037] Among them, f * Validation data set represents S val When the collaborative filter model M at the time of obtaining the minimum value, M is the performance evaluation function, F represents the search space and may include a set of collaborative filtering model, P * He said in the training data set S train When the c...

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Abstract

The invention provides an item recommendation method and system based on a collaborative filtering model, and the method comprises the steps of obtaining a training data set and a collaborative filtering model set; establishing an initial performance prediction model for predicting the model performance of the collaborative filtering model; iteratively updating an established performance prediction model based on the training data set and the collaborative filtering model set; selecting at least one collaborative filtering model from the collaborative filtering model set based on the iteratively updated performance prediction model; and executing item recommendation based on the selected at least one collaborative filtering model.

Description

Technical field [0001] This application relates to user-related recommendation techniques, and more specifically, there is a recommended method and system based on a collaborative filtering model. Background technique [0002] The recommendation system is widely used in various scenarios. For example, the recommendation system can use the e-commerce website to provide product information and recommendations to customers, helping users decide what items should be purchased, and simulate salesperson helped customers to complete the purchase process. Personalized recommendation is based on the characteristics of users and the purchase behavior, and recommend users to be interested in information and goods. Objects can be recommended include goods, advertising, news, music, and more. [0003] Collaborative filtering (CF) is a key technique for the recommendation system for user-related recommendations, for example, to estimate the preference of the user to the item. [0004] In order...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/9536G06N3/08G06Q30/06
CPCG06F16/9535G06F16/9536G06Q30/0631G06N3/08
Inventor 姚权铭
Owner THE FOURTH PARADIGM BEIJING TECH CO LTD
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