Graph structure-based recommendation method, apparatus and device, and storage medium

A recommendation method and a recommendation device technology, applied in the information field, can solve problems such as unsatisfactory recommendation effect and complex network structure, and achieve the effect of personalized adjustment, easy addition and deletion, and optimized results

Pending Publication Date: 2019-05-21
广州市易杰数码科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when recommending items with many attributes, such as videos and movies, each item can be linked together through different a

Method used

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  • Graph structure-based recommendation method, apparatus and device, and storage medium
  • Graph structure-based recommendation method, apparatus and device, and storage medium
  • Graph structure-based recommendation method, apparatus and device, and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0059] Example one:

[0060] Reference figure 2 , Provides a recommendation method based on graph structure, which is used in figure 1 Take the server in as an example for description, including the following steps:

[0061] S10: Obtain attribute information of each video.

[0062] In this embodiment, a video refers to a video published on its own video or a third-party video website for users to click and watch. The video may include a movie, a documentary, or a TV series. Attribute information refers to information used to record the attributes of the video, for example, the actor information, director information, country information, genre information, and age information of the video.

[0063] Specifically, from the database storing the video, the corresponding attribute information is obtained according to the name of the video.

[0064] S20: Calculate the general similarity between each video pairwise according to the attribute information.

[0065] In this embodiment, the gener...

Example Embodiment

[0130] Embodiment two:

[0131] In one embodiment, a recommendation device with a graph structure is provided, and the recommendation device with a graph structure corresponds to the recommendation method with a graph structure in the foregoing embodiment one-to-one. Such as Figure 7 As shown, the recommendation device with the structure of the figure includes a first acquisition module 10, a first calculation module 20, a generation module 30, a second acquisition module 40, a second calculation module 50, a third calculation module 60, and a recommendation result sending module 70. The detailed description of each functional module is as follows:

[0132] The first obtaining module 10 is used to obtain attribute information of each video;

[0133] The first calculation module 20 is configured to calculate the general similarity between each video pair by pair according to the attribute information;

[0134] The generating module 30 is used to generate a candidate recommendation se...

Example Embodiment

[0155] Embodiment three:

[0156] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 8 Shown. The computer equipment includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device is used to store candidate recommendation sets and user history operation records. The network interface of the computer device is used to communicate with an external terminal through a network connection....

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PUM

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Abstract

The invention relates to a graph structure-based recommendation method, apparatus and device, and a storage medium. The graph structure-based recommendation method comprises the steps of obtaining attribute information of each video; According to the attribute information, calculating the common similarity between every two videos; Generating a candidate recommendation set according to the generalsimilarity; Obtaining a user historical operation record of the user identifier according to the user identifier; Calculating a recommendation weight parameter according to the historical operation record of the user; Calculating the final similarity between each video and the user identifier according to the recommendation weight parameter; And sending a video recommendation result to the user identifier according to the final similarity. The video recommendation method has the effects of improving the video recommendation result and enabling the video recommendation result to be closer to the interest of the user.

Description

technical field [0001] The present invention relates to the technical field of information technology, in particular to a graph structure-based recommendation method, device, equipment and storage medium. Background technique [0002] Most of the existing recommendation algorithms are calculated based on a single one or two attributes, and then the corresponding similarity is obtained. However, when recommending items with many attributes, such as videos and movies, each item can be linked together through different attributes, with different degrees of closeness, the network structure will be very complex, and the recommendation effect is not ideal. Contents of the invention [0003] The purpose of the present invention is to provide a recommendation method, device, device and storage medium based on graph structure to improve the effect of video recommendation results and make video recommendation results more closely related to user interests. [0004] Above-mentioned ...

Claims

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Application Information

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IPC IPC(8): G06F16/735G06F16/9535G06F16/78
CPCY02D10/00
Inventor 陈侃李强陈震廖昭文蒋峥计春光陈维李科润黄露李国顺
Owner 广州市易杰数码科技有限公司
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