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Application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis

A sequential pattern and behavior analysis technology, applied in special data processing applications, marketing, instruments, etc., can solve problems such as single support, reduce mining efficiency, and meaningful knowledge cannot be discovered

Active Publication Date: 2015-04-08
SHANDONG EVAYINFO TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But these algorithms only use the single minimum support, which means that all items have the same frequency of occurrence in the database, that is, all products have the same purchase frequency, but in real life this assumption is obviously It cannot be established, on the contrary, some products are purchased very frequently, while some products are purchased very sparsely
For two types of products, household appliances and daily necessities, the frequency of purchasing household appliances is definitely not as high as daily necessities. If we use a single minimum support, household appliances are likely to be screened out, but in fact there are many brands of household appliances It sells

Method used

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  • Application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis
  • Application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis
  • Application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis

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specific Embodiment approach

[0064] The present invention will be described in detail below in conjunction with the examples, but not limited thereto.

Embodiment

[0066] The application of a multi-support positive and negative sequence pattern in the analysis of customer purchase behavior includes the following steps:

[0067] (1) Define the minimum support of the negative sequence based on multi-support

[0068] MIS(i) indicates the minimum item support of item i, i is a positive item or a negative item; a positive element, that is, a purchased commodity, its minimum support is the minimum support value of item i in the element, and for a negative element, that is For unpurchased goods, use the information of the relevant positive elements to calculate its minimum support:

[0069] for negative elements Where a, b represent a certain commodity, the minimum support of the negative element is:

[0070]

[0071] The minimum support of the negative sequence S based on multiple support is the minimum support value of the elements in the sequence, where the element set in S contains: e 1 ,e 2 ... e r , where the min...

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Abstract

The invention relates to application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis. An efficient algorithm named as E-ms NSP is provided to excavate the multi-supporting-degree based positive and negative sequence modes, the main idea of the algorithm is that firstly an improved MS-GSP algorithm is adopted to excavate the multi-supporting-degree based positive sequence mode, then a method the same as e-NSP is adopted to calculate the supporting degree of a negative sequence candidate mode through a formula, and database re-scanning is not needed. The E-ms NSP is a first multi-supporting-degree based negative sequence mode excavation algorithm without constraint limitation. In application, commodities large in clients' purchasing volume of each category of products are screened out within a certain time period, so that when clients purchase the products, certain similar relevant products high in clients' purchasing frequency can be recommended for others by utilizing the multi-supporting-degree positive and negative sequence modes, transaction opportunities of the clients are increased, website browsers are changed into purchasers, cross-selling capacity is improved, the loyalty index of the clients is improved, and the economic benefit of websites is improved.

Description

technical field [0001] The invention relates to the application of a multi-support positive and negative sequence pattern in the analysis of customer purchase behavior, and belongs to the application technical field of the multi-support positive and negative sequence pattern. Background technique [0002] With the popularity of computers and the Internet, online shopping has become a very popular way of shopping. Online shopping is not just a fashion, it has become an indispensable part of life, especially the young people are more keen on online shopping, a new shopping method. In recent years, online shopping has grown explosively, with geometric growth every year. At the same time, many large-scale e-commerce websites, such as Amazon, Alibaba’s Taobao and Tmall, and JD.com, have accumulated a large number of customer transactions. data. How to make full use of these data to effectively analyze and organize the purchasing behavior of customers, how to understand as many ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/02
Inventor 董祥军徐田田
Owner SHANDONG EVAYINFO TECH CO LTD
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