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Predicting method for user behavior in e-commerce

A technology of e-commerce and forecasting methods, applied in business, data processing applications, electrical digital data processing, etc., can solve problems such as weak forecasting and lack of navigation and arrangement

Inactive Publication Date: 2014-09-24
深圳德锟保税电子商务有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] At present, in large-scale e-commerce websites, the user’s purchase behavior prediction is very weak. The category navigation of the website, recommended products, etc. are displayed to all users in a fixed style, but there is no personalized navigation arrangement and accurate product recommendation.

Method used

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  • Predicting method for user behavior in e-commerce
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  • Predicting method for user behavior in e-commerce

Examples

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Embodiment Construction

[0025] The specific embodiment of the present invention is described in detail below in conjunction with accompanying drawing:

[0026] Such as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 and Figure 6 As shown, a method for predicting user behavior in e-commerce of the present invention is based on MVC and Alpha-beta pruning algorithm to dynamically judge the knowledge mined from data.

[0027] Such as figure 1 , figure 2 and image 3 As shown, the prediction method of user behavior in e-commerce includes the following steps:

[0028] S1. Record all the user's behaviors in the e-commerce system into the database of the e-commerce system. The user's behaviors in the e-commerce system include the user's browsing behavior, user's purchasing behavior and user's shopping cart behavior.

[0029] Wherein, the user’s browsing behavior includes: browsing path records, the time spent on each page, the record of returning to the previous page, top behavior, adverti...

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PUM

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Abstract

The invention discloses a predicting method for user behavior in e-commerce, and belongs to the technical fields of e-commerce and data processing. The predicting method comprises the following steps of S1, recording all behaviors of a user in an e-commerce system to a database of the e-commerce system; S2, carrying out data mining processing on primary data in the database so as to obtain a knowledge base; S3, building an MVC framework according to the knowledge base, according to the pruning algorithm, obtaining a success rate sequence from high to low of a next link by a Controller, removing the links with lower success rates, putting the links with higher success rates at the most marked position of a page, and outputting a corresponding View; S4, after a user click a link, selecting a corresponding score in a game tree by the Controller according to the selection of the user, and storing the score in a data source database and the database of the e-commerce system. Next possible selection of the user can be predicted through the pruning algorithm based on MVC probability, and further, e-commerce purchasing instructions can be provided for the e-commerce and the user.

Description

technical field [0001] The invention relates to the technical field of electronic commerce and data processing, in particular to a method for predicting user behavior in electronic commerce. Background technique [0002] In recent decades, due to the rise of the Internet, many websites and companies have accumulated a large amount of data, but the ability of computers to collect and store data far exceeds the ability to analyze, summarize and extract knowledge from data. In the face of massive data, people hope that computers can automatically and intelligently analyze and extract the knowledge and information contained in it, because people deeply understand that there are valuable information in the accumulated data, and these valuable information are important for business development and science. Research or formulation of policies has significant economic or social benefits, so data mining has attracted the attention of many companies. [0003] Data mining integrates t...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/00
CPCG06F16/9535G06Q30/0202
Inventor 陈秋汝
Owner 深圳德锟保税电子商务有限公司
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