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Faked sales identification method and apparatus, and electronic device

A recognition method and a technology for swiping orders, applied in the computer field, can solve the problems of low recognition accuracy and limited coverage of swiping behavior recognition, and achieve the effect of high accuracy.

Active Publication Date: 2017-09-08
BEIJING SANKUAI ONLINE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] This application provides a method for identifying swiping bills, which solves the problems of limited coverage and low recognition accuracy of swiping bills in the prior art

Method used

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  • Faked sales identification method and apparatus, and electronic device
  • Faked sales identification method and apparatus, and electronic device
  • Faked sales identification method and apparatus, and electronic device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] A method for identifying swiping bills disclosed in this application, such as figure 1 As shown, the method includes: step 100 and step 110.

[0026] Step 100, acquiring user behavior characteristics of merchants.

[0027] During specific implementation, the user behavior characteristics of the merchant to be identified can be acquired according to the behavior logs of all users of the merchant to be identified within a period of time. The user behavior characteristics may only include: user group behavior characteristics, wherein the user group behavior characteristics may only include: behavior pattern characteristics or comment dimensional distribution characteristics, or may include both behavior pattern characteristics and comment dimensional distribution characteristics. Wherein, the behavior pattern characteristic is the distribution probability of the description value describing the preset first behavior; the comment dimension distribution characteristic is th...

Embodiment 2

[0033] A method for identifying swiping orders disclosed in this embodiment, such as figure 2 As shown, the method includes: Step 200 to Step 230.

[0034] Step 200, acquire user behavior characteristics of each merchant based on training samples.

[0035] Wherein, the training samples include: normal behavior samples and swiping behavior samples.

[0036] During specific implementation, a certain number of user behavior samples are selected in advance, and the samples are manually calibrated, and the label of order swiping behavior or normal behavior is set. The selected sample can be the user behavior logs of all users of all merchants under a certain category within a certain period of time, or the user behavior logs of all users of one or several merchants under a certain category within a certain period of time. In order to make the recognition model obtained through training more accurate, preferably, the selected samples are user behavior logs of all users of all mer...

Embodiment 3

[0074] A method for identifying swiping orders disclosed in this embodiment, such as image 3 As shown, the method includes: Step 300 to Step 340.

[0075] Step 300, acquire the behavior characteristics of the merchant's user groups based on the training samples.

[0076] Wherein, the training samples include: normal behavior samples and swiping behavior samples.

[0077] During specific implementation, a certain number of user behavior samples are selected in advance, and the samples are manually calibrated, and the label of order swiping behavior or normal behavior is set. The selected sample can be the user behavior logs of all users of all merchants under a certain category within a certain period of time, or the user behavior logs of all users of one or several merchants under a certain category within a certain period of time. In order to make the recognition model obtained through training more accurate, preferably, the selected samples are user behavior logs of all u...

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Abstract

The invention provides a faked sales identification method, which belongs to the technical field of computers and is used for solving the problems of finite identification coverage range and low identification accuracy of faked sales behaviors in the prior art. The method comprises the steps of obtaining user behavior features of a merchant; and through a pre-trained faked sales identification model, performing faked sales identification on the merchant based on the user behavior features, wherein the user behavior features at least include user group behavior features. According to the method disclosed by the invention, the faked sales merchant is identified based on the user group behavior features; the group homoplasy and cooperativity of the user behaviors of the faked sales merchant are fully considered; and compared with a mode for identifying the faked sales merchant based on information such as user identity information or geometric positions, comment content consistency and the like, the method has higher accuracy.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method and device for identifying swiping bills, and electronic equipment. Background technique [0002] Swiping orders is a way for merchants to pay for someone to pretend to be a customer or the merchant themselves, and to improve the ranking and sales of the online store in a fake shopping method to obtain sales and praise to attract customers. Because the behavior of merchants’ order swiping will improve the ranking of merchants, resulting in the merchant’s information obtained by ordinary users is not true, therefore, it is urgent to detect the behavior of swiping orders and take corresponding measures. In the prior art, methods for detecting swiping behavior mainly include: Agent-Based posting robot detection and identification, and account identification based on user trusted identities (such as phone numbers, bank account numbers, Alipay, etc.). AgentBased ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/00
CPCG06Q30/0185
Inventor 曾轲李露龚能王翰森
Owner BEIJING SANKUAI ONLINE TECH CO LTD
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