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Donation behavior and donor retention prediction method for crowdfunding platform

A forecasting method, the technology of the donor, applied in the field of machine learning, can solve the problems of limited research and technical methods, and achieve the effect of reducing the churn rate of users

Inactive Publication Date: 2018-11-16
UNIV OF SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for a long time, there have been limited research and technical approaches to donor behavior and donor retention

Method used

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  • Donation behavior and donor retention prediction method for crowdfunding platform
  • Donation behavior and donor retention prediction method for crowdfunding platform
  • Donation behavior and donor retention prediction method for crowdfunding platform

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Embodiment Construction

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0017] Embodiments of the present invention provide a crowdfunding platform-oriented donation behavior and donor retention prediction method, such as figure 1 As shown, it mainly includes:

[0018] Step 1. Crawl project data from the crowdfunding platform.

[0019] Step 2. After performing feature extraction and preprocessing on the crawled project data, divide the data into intervals according to time.

[0020] Step 3. Construct a joint deep sur...

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Abstract

The invention discloses a donation behavior and donor retention prediction method for a crowdfunding platform, comprising: crawling project data from the crowdfunding platform; dividing data intervalsaccording to time after performing feature extraction and preprocessing on the crawled project data; constructing a joint deep survival model by the donation behavior sequence and survival preservation sequence of the donor, and the features after the data interval division corresponding to the donor; and optimizing the joint deep survival model by combining the designed order constraint functionto predict the donation behavior and the survival maintenance state of the donor. By using the Joint Deep Survival Model (JDS) to model behaviors of the donors, the method may effectively predict whether the donors on the crowdfunding platform are lost, thereby reminding the platform to make measures to reduce the user lost rate, having certain practical application value, and bringing certain potential economic benefits to the platform.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular to a crowdfunding platform-oriented donation behavior and donor retention prediction method. Background technique [0002] In recent years, crowdfunding platforms have developed rapidly, among which donation-based crowdfunding platforms have become more and more popular and popular. Using the Internet as a medium can achieve large-scale microfinancing. Therefore, the crowdfunding mechanism has brought new vitality to charity and helped many people with dreams and difficulties. However, the serious attrition of donors is an important common problem faced by crowdfunding platforms and traditional philanthropy. In fact, due to its non-profit nature, the loss of donors in donation-based crowdfunding and traditional charitable activities is very serious. According to statistics, the loss rate of donation customers in charity crowdfunding is over 70%. Therefore, it is very mea...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q30/02G06F17/30G06Q40/06
CPCG06Q10/04G06Q30/0202G06Q40/06
Inventor 陈恩红刘淇赵洪科金斌斌陶汉卿
Owner UNIV OF SCI & TECH OF CHINA
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