Knowledge graph-based recommendation method and device, computer equipment and storage medium

A technology of knowledge graph and recommendation method, which is applied in the fields of recommendation method, device, computer equipment and storage medium based on knowledge graph, and can solve the problem of not being able to recommend results with high efficiency and low cost.

Active Publication Date: 2020-11-20
ONE CONNECT SMART TECH CO LTD SHENZHEN
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] In view of this, the present invention proposes a recommendation method, device, computer equipment and storage medium based on knowledge graphs, which are used to solve the relationship be

Method used

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  • Knowledge graph-based recommendation method and device, computer equipment and storage medium
  • Knowledge graph-based recommendation method and device, computer equipment and storage medium
  • Knowledge graph-based recommendation method and device, computer equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] A recommendation method based on a knowledge map in this embodiment, by performing probability calculations on multiple random jumps of knowledge map nodes, can start from a single node and obtain the relationship strength value from this node to all others through multiple calculations. Then select the nodes that meet the preset relationship strength value to generate the recommended path, which solves the problem of not being able to obtain accurate recommendation results with high efficiency and low cost.

[0058] Please refer to figure 2 , a recommendation method based on a knowledge map of this embodiment, the knowledge map includes a plurality of nodes, including the following steps:

[0059] Step S100, generate the user attribute node of the knowledge graph according to the user attribute table, generate the product attribute node of the knowledge graph according to the product attribute table, the user attribute table includes the user's product purchase histor...

Embodiment 2

[0140] read on Figure 5 , shows a schematic diagram of program modules of the knowledge map-based recommendation device of the present invention. In this embodiment, the knowledge map-based recommendation device 20 may include or be divided into one or more program modules, one or more program modules are stored in a storage medium and executed by one or more processors, In order to complete the present invention, and realize the above-mentioned recommendation method based on knowledge map. The program module referred to in the embodiment of the present invention refers to a series of computer program instruction segments capable of completing specific functions, which is more suitable than the program itself to describe the execution process of the knowledge map-based recommendation device 20 in the storage medium. The following description will specifically introduce the functions of each program module of the present embodiment:

[0141] The weight calculation module 202...

Embodiment 3

[0145] refer to Figure 6 , is a schematic diagram of the hardware architecture of the computer device according to Embodiment 3 of the present invention. In this embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and / or information processing according to preset or stored instructions. The computer device 2 may be a rack server, a blade server, a tower server or a cabinet server (including an independent server, or a server cluster composed of multiple servers) and the like. Such as Figure 6 As shown, the computer device 2 at least includes, but is not limited to, a memory 21 , a processor 22 , a network interface 23 , and a recommendation device 20 based on knowledge graphs that can communicate with each other through a system bus. in:

[0146] In this embodiment, the memory 21 includes at least one type of computer-readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia ca...

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PUM

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Abstract

The invention discloses a knowledge graph-based recommendation method and device, computer equipment and a storage medium. The method comprises the following steps: determining a to-be-analyzed node in the plurality of nodes, setting a relationship weight value between the to-be-analyzed node and a first-layer neighbor node as a, and randomly calculating a relationship weight value I from any neighbor node of the to-be-analyzed node to an Lth-layer node of the to-be-analyzed node, wherein I = a-(L-1) * (a/6); selecting the node of which the relationship weight value from the to-be-analyzed node to other nodes is greater than a preset value to generate a recommended path; generating recommendation data between the to-be-analyzed node and other nodes according to the recommendation path. According to the method, the knowledge graph nodes are randomly calculated for multiple times, the relationship strength values of the other nodes are obtained from the single node, then the nodes meeting the preset relationship strength value are selected to generate the recommendation path, and therefore the problem that an accurate recommendation result cannot be obtained with high efficiency andlow cost is solved.

Description

technical field [0001] The present invention relates to the field of data knowledge graphs, in particular to a recommendation method, device, computer equipment and storage medium based on knowledge graphs. Background technique [0002] In a recommendation system based on knowledge graphs, it is necessary to calculate the relationship strength between network nodes, so as to obtain recommendation results based on the correlation between network nodes. When calculating the relationship strength between network nodes, path search, similarity between nodes, etc. are usually used. A variety of methods, among which the method of path search, can better reflect the relationship between two points, and plays an important role in the calculation of relationship strength and relationship prediction. [0003] Existing path search methods mainly include: [0004] When the shortest path is used to measure the strength of the relationship between two points, the path information that re...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06F16/36
CPCG06F16/9535G06F16/367
Inventor 曹合心
Owner ONE CONNECT SMART TECH CO LTD SHENZHEN
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