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Interest point POI recommendation model training method and device and electronic equipment

A training method, a technology of points of interest, applied in the field of devices and electronic equipment, the field of training methods of POI recommendation models for points of interest, can solve the problems of low accuracy and low POI accuracy, and achieve the effect of improving accuracy

Pending Publication Date: 2020-12-22
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the prior art, when recommending POIs to users based on the POI recommendation model, the existing POI recommendation model regards all POIs as individual individuals for recommendation. Due to the low accuracy of the existing POI recommendation model, the When POI recommendation is performed based on a POI recommendation model with low accuracy, it will also lead to low accuracy of POI recommendation

Method used

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  • Interest point POI recommendation model training method and device and electronic equipment
  • Interest point POI recommendation model training method and device and electronic equipment
  • Interest point POI recommendation model training method and device and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] figure 2 It is a schematic flowchart of a training method for a point of interest POI recommendation model provided according to the first embodiment of the present application. The training method for the point of interest POI recommendation model can be executed by software and / or hardware devices. For example, the hardware device can be a point of interest A training device for a POI recommendation model. The training device for a POI recommendation model for a point of interest may be an electronic device. For example, see figure 2 Shown, the training method of this point of interest POI recommendation model can comprise:

[0039] S201. Collect POI sample data.

[0040] For example, the POI sample data includes identifiers of multiple POIs, and may also include location information of each POI.

[0041] S202. Respectively acquire preference information of multiple users for POIs in the POI sample data, and relationships between POIs at different levels in the P...

Embodiment 2

[0056] Figure 4 It is a schematic flow chart of obtaining the preference information of multiple users for POIs according to the second embodiment of the present application. The method for obtaining the preference information of multiple users for POIs can also be executed by software and / or hardware devices, for example, the hardware The device may be a training device for a POI recommendation model. For example, see Figure 4 As shown, the method for obtaining the preference information of the plurality of users to POIs may include:

[0057] S401. Obtain attribute information of multiple users respectively, and obtain access data of each user to a POI having the same type information of the POI.

[0058] For example, the user's attribute information may include information such as the user's age, nationality, or education background, and may also include other information. Here, the embodiment of the present application only uses the user's attribute information to inclu...

Embodiment 3

[0078] Figure 5 It is a schematic flowchart of obtaining the relationship between POIs at different levels according to the third embodiment of the present application. The method for obtaining the relationship between POIs at different levels can also be executed by software and / or hardware devices, for example, the hardware The device may be a training device for a POI recommendation model. For example, see Figure 5 As shown, the method for obtaining the relationship between POIs at different levels may include:

[0079] S501. Acquire type information of POIs in each layer, and obtain access data that each POI in each layer of POIs is accessed by a user having the same attribute information as a plurality of users.

[0080] For example, the type information of the POI can be whether the POI is located in a park, or whether the access data of the POI visited every day meets the preset conditions, and can also include other information. Here, in the embodiment of the prese...

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Abstract

The invention discloses an interest point POI recommendation model training method and device and electronic equipment and relates to the technical field of artificial intelligence and big data. The method is characterized in that when a POI recommendation model is trained and generated, considering that the POI recommendation accuracy is influenced by the preference information of a user for POIsand the relationship between POIs of different levels, when the POI recommendation model is trained and generated, the preference information of the user for the POIs and the relationship between thePOIs of different levels are obtained firstly, and then POI recommendation accuracy is improved. According to the POI recommendation method and device, the generated POI recommendation model is trained according to the preference information of the user for the POI and the relationship between the POIs of different levels, so that the accuracy of the POI recommendation model is improved, and POIrecommendation accuracy can be effectively improved when POI recommendation is performed based on the POI recommendation model with relatively high accuracy.

Description

technical field [0001] The present application relates to the technical fields of artificial intelligence and big data, and in particular to a training method, device and electronic equipment for a point of interest POI recommendation model. Background technique [0002] Point Of Interest (POI) generally refers to all geographical objects that can be abstracted as points, especially some geographical entities that are closely related to people's lives, such as schools, banks, restaurants, gas stations, hospitals or supermarkets. The main function of POI recommendation is to recommend specific points of interest to users based on the POI recommendation model, such as restaurants, hotels, scenic spots, etc., so as to provide convenience for users. [0003] In the prior art, when recommending POIs to users based on the POI recommendation model, the existing POI recommendation model regards all POIs as individual individuals for recommendation. Due to the low accuracy of the exi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9537G06N20/00
CPCG06F16/9537G06N20/00G01C21/3679G01C21/3811G06N5/022G01C21/3461G01C21/3476G01C21/3617
Inventor 周景博熊辉
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD