Interpretable recommendation modeltraining method and device

A model training and interpretive technology, applied in the field of artificial intelligence, can solve the problems of insufficient persuasion of recommendation system and insufficient robustness of explanation, and achieve the effect of promoting implementation and improving robustness.

Active Publication Date: 2021-09-07
UNIV OF SCI & TECH OF CHINA
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  • Application Information

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Problems solved by technology

[0004] In view of this, the present disclosure provides an explainable recommendation model training method and device to solve the problems in

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  • Interpretable recommendation modeltraining method and device
  • Interpretable recommendation modeltraining method and device
  • Interpretable recommendation modeltraining method and device

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Embodiment Construction

[0021] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. It should be understood, however, that these descriptions are exemplary only, and are not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concepts of the present disclosure.

[0022] In the technical solution of the present disclosure, the acquisition, storage and application of the user's personal information involved are in compliance with relevant laws and regulations, necessary confidentiality measures have been taken, and t...

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Abstract

The invention provides an interpretable recommendation model training method and device. The method comprises the following steps: obtaining a time sequence of user behaviors of multiple users; processing an initial knowledge graph based on the time sequence to obtain a time sequence knowledge graph; obtaining the feature vectors of the time sequence knowledge graph by embedding a joint learning model, wherein the feature vectors comprise entity feature vectors and relation feature vectors; and training an initial model according to the feature vectors to obtain a target recommendation model.

Description

technical field [0001] The present disclosure relates to the field of artificial intelligence, and more specifically, to an interpretable recommendation model training method and an interpretable recommendation model training device. Background technique [0002] Today, with the rapid development of information technology, the recommendation system can filter content and make decisions for billions of Internet users, such as electronic shopping, listening to music, watching videos, etc. [0003] In the process of implementing the disclosed concept, the inventors found that the explainability of the current recommendation system is low, resulting in poor user experience. Contents of the invention [0004] In view of this, the present disclosure provides an interpretable recommendation model training method and device to solve the problems in the related art that the explanation path of the recommendation system is not sufficiently persuasive and the explanation is not robus...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/28G06F40/30G06K9/62G06N20/00
CPCG06F16/9535G06F16/288G06F40/30G06N20/00G06F18/23
Inventor 赵愉悦谢海永吴曼青
Owner UNIV OF SCI & TECH OF CHINA
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