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Method and device for performing sample domain conversion on training samples of recommendation model

A technology of training samples and samples, applied in the field of machine learning, can solve problems such as small number of samples and insufficient number of samples to reach cold start

Active Publication Date: 2022-06-21
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For new scenarios, the corresponding number of samples will be less, and even the number of samples cannot meet the requirements of cold start.

Method used

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  • Method and device for performing sample domain conversion on training samples of recommendation model
  • Method and device for performing sample domain conversion on training samples of recommendation model
  • Method and device for performing sample domain conversion on training samples of recommendation model

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Embodiment Construction

[0029] The subject matter described herein will be discussed below with reference to example embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and not to limit the scope of protection, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements discussed without departing from the scope of the description. Various examples may omit, substitute, or add various procedures or components as desired. Additionally, features described with respect to some examples may also be combined in other examples.

[0030] As used herein, the term "including" and variations thereof represent open-ended terms meaning "including but not limited to". The term "based on" means "based at least in part on". The terms "one embodiment" and "an embodiment" mean "at least one embodiment." The term "another embod...

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Abstract

The embodiment of this specification provides a method and device for performing sample domain conversion on training samples. In this method, the first training sample under the first sample domain and the second training sample under the second sample domain are acquired , using the first sample migration transformation process to migrate and transform the second training sample into a third training sample, wherein the first sample migration transformation process is implemented under the first constraint condition by using a machine learning method. The third training sample is determined as a training sample under the first sample domain when the first constraint condition is satisfied.

Description

technical field [0001] The embodiments of the present specification relate to the technical field of machine learning, and in particular, to a method and apparatus for performing sample domain conversion on training samples of a recommendation model. Background technique [0002] The samples in each scenario can reflect the business characteristics of the scenario. Based on this, the samples in different scenarios will be different. For example, various business models such as "Double Eleven" and "Mobile Festival" launched in the new retail era to meet the shopping needs of the public, each business model is a scene, and different business models have different business characteristics. For example, the targeted consumer groups and product types are different, so different business models require different samples for cold start. The samples are mainly clothing and so on. [0003] For more mature scenarios, the number of samples is more abundant. For new scenarios, the co...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/214
Inventor 王冠楠
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD