Content recommendation method and apparatus based on depth reinforcement learning

A technology of reinforcement learning and content recommendation, applied in the Internet field to achieve the effect of excellent recommendation results

Active Publication Date: 2018-12-21
云南腾云信息产业有限公司
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  • Abstract
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Problems solved by technology

In many application scenarios, it is necessary to provide users with multiple recommended content, that is, it is necessary to provide users with a combination of recomme

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  • Content recommendation method and apparatus based on depth reinforcement learning
  • Content recommendation method and apparatus based on depth reinforcement learning
  • Content recommendation method and apparatus based on depth reinforcement learning

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Embodiment Construction

[0035] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0036] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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Abstract

The invention provides a content recommendation method and a device based on depth reinforcement learning. The method comprises the following steps: training a depth reinforcement function to obtain atraining result for a parameter set in the depth reinforcement function; obtaining an ordered candidate set of recommended contents and a number of pieces of selected recommended contents; based on the training results of the parameter set, the comprehensive reward value of each recommended content in the candidate set being calculated by using the depth enhancement function; a comprehensive award value for each recommendation content being associated with the recommendation content and other recommendations ranked after the recommendation content; according to the result of calculation, selecting the recommended contents as the selected contents and outputting them in order. The invention synthetically considers the recommended content and the ranking of the recommended content by usingthe method of depth reinforcement learning, thereby obtaining a better recommended result.

Description

technical field [0001] The present invention relates to the field of Internet technology, in particular to a content recommendation method and device based on deep reinforcement learning. Background technique [0002] In order to accurately locate target data of interest to users in massive data, various content recommendation methods are provided in the prior art. For example, Facebook adopts a hybrid sorting method of GBDT and logistic regression, Google adopts a wide and deep machine learning sorting method based on deep learning, and Netflix adopts a machine learning sorting method based on session information using RNN. However, the above methods for content recommendation all belong to the single content recommendation method of logistic regression. This single content recommendation method takes the maximization of the expected effect of the selected single recommended content as the recommendation goal, and does not take into consideration the relationship between t...

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Application Information

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IPC IPC(8): G06F17/30G06N99/00
Inventor 王瑞夏锋林乐宇
Owner 云南腾云信息产业有限公司
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