Resource distribution method and device and electronic equipment

A resource allocation and resource technology, applied in the computer field, can solve problems such as low allocation accuracy, and achieve the effect of improving accuracy and resource utilization efficiency

Pending Publication Date: 2018-04-20
BEIJING SANKUAI ONLINE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present application provides a resource allocation method to solve the problem of low allocation accuracy existing in resource allocation methods in the prior art

Method used

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  • Resource distribution method and device and electronic equipment
  • Resource distribution method and device and electronic equipment
  • Resource distribution method and device and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027] A resource allocation method disclosed in this application, such as figure 1 As shown, the method includes: step 100 to step 120.

[0028] In step 100, the user's order rate with resources and order rate without resources is estimated by the order rate estimation model.

[0029] In the actual implementation of this application, the order rate prediction model must first be trained according to the user's historical behavior data, user portrait data, and user's own resource data. During specific implementation, some user features are extracted according to the user’s historical behavior data (for example: user behavior features of preset behaviors), and the label data is extracted according to the order data in the user’s historical behavior data, and some user profiles are extracted according to the user portrait data. Features (for example: user portrait features), extract some user features (for example: resource features) according to the user's own resource data; t...

Embodiment 2

[0037] A resource allocation method disclosed in this application, such as figure 2 As shown, the method includes: Step 200 to Step 230.

[0038] Step 200, based on the user's historical behavior data, user profile data, and user owned resource data, train an order rate prediction model.

[0039] During specific implementation, based on the user's historical behavior data, user portrait data, and user owned resource data, the order rate prediction model is trained, including: training the order rate prediction model based on the first user characteristic data and the first label data ; Wherein, the first user characteristic data includes: user behavior characteristics of preset behaviors, user portrait characteristics, and resource characteristics used to indicate that the user owns resources; the first tag data is used to indicate whether the user places an order; the The user behavior characteristics of the preset behavior are obtained according to the user's historical be...

Embodiment 3

[0066] A resource allocation method disclosed in this application, such as image 3 As shown, the method includes: Step 300 to Step 350.

[0067] Step 300, based on the user's historical behavior data, user portrait data, and user owned resource data, train an order rate prediction model.

[0068] Based on the user's historical behavior data, user portrait data, and user-owned resource data, see Embodiment 2 for training an order rate prediction model, and details will not be repeated here.

[0069]Step 310, based on the historical behavior data and user profile data of users who own resources, train an order price prediction model.

[0070] During specific implementation, based on the historical behavior data and user portrait data of users who own resources, train the order price prediction model, including: according to the second user characteristic data and second label data of users who own resources, train the order price prediction model Estimation model; wherein, th...

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PUM

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Abstract

The invention provides a resource distribution method, belongs to the technical field of computers, and solves a problem that a resource distribution method in the prior art is low in distribution precision. The method comprises the steps: pre-estimating resource ordering rates and no-resource ordering rates of users through an ordering pre-estimation model; determining the resource benefits corresponding to the users based on the resource ordering rates and the no-resource ordering rates; and carrying out the resource distribution for the corresponding users according to a sequence of resource benefits from the high to the low. According to the invention, the method achieves the resource distribution according to the resource benefits, can effectively improve the utilization rate of resources, and improves the resource distribution accuracy.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a resource allocation method and device, and electronic equipment. Background technique [0002] With the development of Internet technology, more and more network platforms have emerged. In order to improve the user stickiness of the platform or product, the platform usually allocates some resources on the platform to users to enhance the stickiness of registered users and attract new users. In the prior art, modeling is usually performed based on order placement rates based on historical data, and then the trained model is used to determine which users to allocate resources to. Or, according to the preset resource allocation strategy, resources are only allocated to users whose order placing rate meets the preset threshold range, for example, only resources are allocated to users whose order placing rate is less than 0.5. However, after long-term data collection a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q30/02G06Q30/06
CPCG06Q10/04G06Q10/0631G06Q30/0224G06Q30/0635
Inventor 左元付晴川吕兵
Owner BEIJING SANKUAI ONLINE TECH CO LTD
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