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Personalized recommendation system based on deep learning

A recommendation system and deep learning technology, applied in the field of video recommendation system design, to achieve the effect of improving satisfaction and clear and smooth video playback

Pending Publication Date: 2022-07-12
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

A large amount of information meets the needs of users for information, but it also brings problems: how to select the information you need or are interested in from the massive data? For video sites, it is necessary to recommend information to attract users

Method used

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  • Personalized recommendation system based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] Example 1, refer to figure 1 , a personalized recommendation system based on deep learning, including a user interest module, a recommendation object module and a recommendation algorithm module, wherein,

[0026] Module 1 (user interest module) mainly has the following three ways:

[0027] Method (1) The personal information filled in by the user during registration is mainly the user's name, occupation, date of birth, personal income, highest education, etc.;

[0028] Mode (2) Information provided by the user voluntarily and voluntarily: the information is the content actively input by the user in the search box, and the content usually reflects the user's personal needs. It also includes the user's rating of the video after watching, reflecting the user's satisfaction;

[0029] Mode (3) Information left by the user's operation behavior: The system records the number of times, frequency, dwell time, etc. of the user's browsing content, which can reflect the user's p...

Embodiment 2

[0033] Example 2, refer to figure 1 , this embodiment is optimized on the basis of Embodiment 1, specifically:

[0034] A personalized recommendation system based on deep learning, including a user interest module, a recommendation object module and a recommendation algorithm module, wherein,

[0035] Module 1 (user interest module) mainly has the following three ways:

[0036] Method (1) The personal information filled in by the user during registration is mainly the user's name, occupation, date of birth, personal income, highest education, etc.;

[0037] Mode (2) Information provided by the user voluntarily and voluntarily: the information is the content actively input by the user in the search box, and the content usually reflects the user's personal needs. It also includes the user's rating of the video after watching, reflecting the user's satisfaction;

[0038] Mode (3) Information left by the user's operation behavior: The system records the number of times, frequen...

Embodiment 3

[0042] Example 3, refer to figure 1 , this embodiment is optimized on the basis of Embodiment 1, specifically:

[0043] A personalized recommendation system based on deep learning, including a user interest module, a recommendation object module and a recommendation algorithm module, wherein,

[0044] Module 1 (user interest module) mainly has the following three ways:

[0045] Method (1) The personal information filled in by the user during registration is mainly the user's name, occupation, date of birth, personal income, highest education, etc.;

[0046] Mode (2) Information provided by the user voluntarily and voluntarily: the information is the content actively input by the user in the search box, and the content usually reflects the user's personal needs. It also includes the user's rating of the video after watching, reflecting the user's satisfaction;

[0047] Mode (3) Information left by the user's operation behavior: The system records the number of times, frequen...

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Abstract

The invention belongs to the technical field of video recommendation system design, particularly relates to a personalized recommendation system based on deep learning, and aims to solve the problem that it is difficult for a user to select favorite contents from massive videos in the background technology, and the personalized recommendation system comprises a user interest module, a recommendation object module and a recommendation algorithm module, the module 1 (the user interest module) mainly has the following three modes: (1) personal information filled during registration of a user mainly comprises the name of the user, the occupational area of the user, the birth month, the personal income, the highest education background and the like; according to the system, the leading network video transmission technology is adopted, videos are played clearly and smoothly, the website comprises mass video content, the video content can be continuously updated, and a personalized video recommendation system is designed for the video website for solving the problem that a user is difficult to select favorite content from the mass videos, so that the user experience is improved. The required video is recommended to the user, and the satisfaction degree of the user to the website is improved.

Description

technical field [0001] The invention relates to the technical field of video recommendation system design, in particular to a deep learning-based personalized recommendation system. Background technique [0002] With the popularization of the Internet, today's society has moved from the era of lack of information to the era of information overload. A large amount of information meets the needs of users for information, but it also brings problems: how to select the information that you need or are interested in from the massive data? For video sites, information needs to be selected to attract users. [0003] With the development of the Internet, there are countless video websites, and the number of videos on the website has completely exceeded the amount of videos that users can watch, and there are still many videos that users are not interested in at all. In order to solve this problem , people have developed a personalized recommendation system. SUMMARY OF THE INVENT...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/735G06F16/75G06F16/78G06F16/9535G06F16/9536
CPCG06F16/735G06F16/75G06F16/7867G06F16/9535G06F16/9536
Inventor 王诗卿战荫伟
Owner GUANGDONG UNIV OF TECH
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