Recommendation model training method and training apparatus

A training method and model technology, applied in the computer field, can solve problems such as unbalanced distribution, sparse data labeling, and sparse adoption, and achieve the effects of improving accuracy, alleviating imbalance, and good generalization performance

Pending Publication Date: 2017-10-20
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] 1. At present, most recommendation systems affect the recommendation results by inputting user behavior data as a sample feature into the recommendation model, but there is no specific reference standard for whether the recommendation results are recognized by customers and whether the recommendation mod

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  • Recommendation model training method and training apparatus
  • Recommendation model training method and training apparatus
  • Recommendation model training method and training apparatus

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0063] Embodiment 1: Take the current common commodity recommendation as an example to introduce the specific implementation process of the technical solution of the present invention.

[0064] figure 2 It is a system architecture diagram of Embodiment 1 of the present invention. Such as figure 2 As shown, the recommendation model of Embodiment 1 of the present invention is used in a commodity recommendation system. The commodity recommendation system mainly includes an online real-time recommendation part and an offline recommendation model training part.

[0065] Among them, the online real-time recommendation process is: according to the online user's real-time recommendation request, the recommendation engine filters and sorts candidate product data according to the offline trained recommendation model, and returns the determined recommendation result to the user. Among them, the screening of product data can remove invalid or sensitive recommendation results (such as: produ...

Example Embodiment

[0085] Embodiment 2: Taking the currently commonly used search engine recommendation as an example to introduce the specific implementation process of the technical solution of the present invention.

[0086] Similar to the first embodiment, the recommendation system of the search engine mainly includes an online real-time recommendation part and an offline recommendation model training part.

[0087] Among them, the online real-time recommendation process is: when the user enters a search keyword in the input box, the recommendation system calls the recommendation engine according to the online user's real-time recommendation request, and the recommendation engine recommends the candidate recommendation result data according to the offline trained recommendation model Perform operations such as filtering and sorting, and return the determined recommendation results to the user.

[0088] In order to use the result feedback after recommendation for the optimization of the recommendati...

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Abstract

The present invention provides a recommendation model training method and training apparatus, which can take the behavior of the user after the recommendation result is displayed as recommendation feedback, and can effectively alleviate the sparseness of the acceptation amount in the training data compared with the recommended amount and the imbalance of the proportion of the positive and negative samples. The recommendation model training method comprises: obtaining training data of a recommendation model, wherein the training data is the data generated in the latest time period, and the latest time period has a predefined time length; marking the training data according to the predetermined training data marking rule to obtain the latest marked data, wherein the latest marked data comprises the user feedback after the recommendation result of the latest time period is displayed, and the user feedback is determined according to the user behavior after the recommendation result is displayed; and training the latest marked data to obtain the recommendation model.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a training method and training device for a recommendation model. Background technique [0002] Recommendation is an important way for information promotion to enable people to obtain information, and it is applied in all aspects of life, such as: search engine recommendation, input word recommendation, website information recommendation, and friend circle information recommendation, commodity Recommend and more. By analyzing and processing the collected user information to generate a recommendation model, user recommendations can be made more conveniently, quickly and accurately. [0003] Take a search engine as an example. When a user enters a keyword, the search engine will use the recommendation model trained and produced based on the search records of other users recorded on the website to make recommendations to the user. For example: when the user enters the keyword "JA...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/951G06F18/214
Inventor 白露杨大利汪鑫郭文涛
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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