Method for detecting abusive transactions due to price fluctuation, information processing device, and computer-readable recording medium

Abstract

This invention relates to a method, information processing apparatus, and computer-readable recording medium for detecting unfair transactions based on price changes. The unfair transaction detection method is used to detect unfair transactions on an e-commerce system and may include the following steps: acquiring product price change information and user behavior information related to the product price change information; using an unfair transaction detection model, determining whether a first transaction corresponding to the user behavior information is equivalent to an unfair transaction based on the product price change information and the user behavior information; and, in response to determining that the first transaction is an unfair transaction, changing the price of the first transaction again.

Claims

1. A method for detecting abusive transactions, executed by at least one processor, for detecting abusive transactions on an e-commerce system, wherein, The method includes the following steps: obtaining product price change information and user behavior information related to the product price change information; generating an unfair transaction detection model, which includes the following steps: obtaining labeled data, which serves as correct answer data and is related to determining whether each transaction corresponding to the user's pre-learning behavior information is equivalent to an unfair transaction based on the product's pre-learning price change information, wherein the step of obtaining the labeled data further includes the following steps: outputting the user's pre-learning behavior information and the product's pre-learning price change information; and receiving user input related to the unfair transaction possibility score of each transaction, or user input related to whether each transaction is equivalent to an unfair transaction; using the unfair transaction detection model, determining whether a first transaction corresponding to the user behavior information is equivalent to an unfair transaction based on the product price change information and the user behavior information; and responding to the determination that the first transaction is an unfair transaction, changing the price of the first transaction again.

2. As in Request 1, the method for detecting improper transactions, wherein, The product price change information includes at least one of the following: the product price before the change, the current product price, the time of the price change, the current product cost price, or the current product price from competitors.

3. As in Request 2, the method for detecting improper transactions, wherein, The method further includes the following steps: obtaining product-related information, which includes at least one of product identification information, product name, or product category.

4. As in Request 1, the method for detecting improper transactions, wherein, The user behavior information includes at least one of product inquiry, order generation, payment, or return.

5. As in request item 4, the method for detecting improper transactions, wherein, The method further includes the following steps: obtaining user information, wherein the user information includes at least one of user identification information, user name, user email address, Internet Protocol address, device identification information, or user transaction history.

6. As in Request 1, the method for detecting improper transactions, wherein, The method further includes the following steps: in response to the determination that the first transaction is an improper transaction, indicating that the price change of the product corresponding to the first transaction is caused by an error.

7. As in Request 1, the method for detecting improper transactions, wherein, The method further includes the following steps: if the current price is lower than the product cost price, then the price is changed again based on the product's price change information.

8. As in Request 1, the method for detecting improper transactions, wherein, The step of detecting whether it is equivalent to the unfair transaction further includes the following steps: if the difference between the current product price and the price of the current product from the competing company is within a specified range, it is determined that it is not an unfair transaction.

9. As in Request 1, the method for detecting improper transactions, wherein, The step of changing the price again includes the following steps: restoring the product price related to the first transaction to the existing price.

10. The method for detecting improper transactions as described in Request 1, wherein, The steps for generating the unfair transaction detection model further include the following steps: obtaining pre-learning price change information of the product and pre-learning behavior information of the user; and pre-learning model based on the pre-learning price change information of the product, the pre-learning behavior information of the user, and the labeled data.

11. A computer-readable recording medium, wherein, The computer program contains a method for performing any of the requests 1 to 10 on the computer.

12. An information processing apparatus, wherein, include: Communication module; Memory; The system also includes at least one processor connected to the memory for executing at least one computer-readable program included in the memory, the at least one program including instructions to perform the following steps: acquiring price change information of a product and user behavior information related to the price change information of the product; generating an unfair transaction detection model, including instructions to perform the following steps: acquiring marker data, the marker data serving as correct answer data and related to determining whether each transaction corresponding to the user's pre-learning behavior information is equivalent to an unfair transaction based on the product's pre-learning price change information, wherein the instructions to acquire the marker data further include instructions to perform the following steps: outputting the user's pre-learning behavior information and the product's pre-learning price change information; and receiving user input related to the unfair transaction possibility score of each transaction, or user input related to whether each transaction is equivalent to an unfair transaction; using the unfair transaction detection model, determining whether a first transaction corresponding to the user behavior information is equivalent to an unfair transaction based on the product's price change information and the user behavior information; and in response to determining that the first transaction is an unfair transaction, changing the price change of the first transaction again.

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