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Fraud Mining Method for Multidimensional Sparse Sales Data Warehouse

A sales data and multi-dimensional data technology, applied in the field of fraudulent behavior mining, can solve problems such as difficult to work effectively

Active Publication Date: 2021-02-09
CHENGDU UNIV OF INFORMATION TECH +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

So the mixture of normal extremum and abnormal extremum will make it difficult for traditional methods based on extremum anomaly detection to work effectively

Method used

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  • Fraud Mining Method for Multidimensional Sparse Sales Data Warehouse
  • Fraud Mining Method for Multidimensional Sparse Sales Data Warehouse
  • Fraud Mining Method for Multidimensional Sparse Sales Data Warehouse

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Embodiment Construction

[0076] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0077] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...

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Abstract

The invention relates to a fraud mining method for a multi-dimensional sparse sales data warehouse, which belongs to the field of data mining. The method includes the following steps: S1: define parameters, including multidimensional data space, partial order lattice on the multidimensional data space, sales data warehouse, data partitioning of the sales data warehouse on the multidimensional data space, pending order behavior and pending order mode; S2 : Define the problem; S3: Mining the pending order points under the specific pending order mode; S4: Mining the pending order mode. The present invention proposes the concept of the partial sequence lattice of the pending order pattern. By introducing the relative position and partial sequence structure information of each pending order pattern in the partial sequence lattice, the dimension level information in the data warehouse is effectively used to carry out the execution of the pending order pattern followed by the pending order behavior. dig.

Description

technical field [0001] The invention belongs to the field of data mining, and relates to a method for mining fraudulent behaviors facing a multi-dimensional sparse sales data warehouse. Background technique [0002] In the era of mobile Internet, more and more transactions and operations have been transferred online, and various fraudulent activities have emerged. In the e-commerce industry, there is a phenomenon of fraudulent billing, in the public service industry, there is a phenomenon of scalpers, and in the O2O industry, there is a phenomenon of junk accounts. These fraudulent behaviors have formed the so-called "black industry". Make profits through commercial loopholes in the industry online and offline. Similar commercial frauds also occur in distribution channel systems. In this system, big brand companies will not sell their products directly to consumers, but choose some distributors to sell their products to end customers, and have developed a series of incenti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/02G06F16/2458G06F16/28
CPCG06Q30/0225G06F16/2465G06F16/283
Inventor 乔少杰郑皎凌程维杰韩楠宋学江张小辉叶青魏军林肖月强陈权亮李斌勇张吉烈张永清何林波温敏元昌安彭京周凯余华范勇强冉先进
Owner CHENGDU UNIV OF INFORMATION TECH