CN-121981744-A - Data processing method, device and program product based on second-hand electronic equipment

CN121981744ACN 121981744 ACN121981744 ACN 121981744ACN-121981744-A

Abstract

The application relates to a data processing method, device and program product based on second-hand electronic equipment. The method comprises the steps of grouping second-hand electronic equipment to obtain a plurality of second-hand electronic equipment groups, determining respective representative prices of the second-hand electronic equipment groups on each date in a preset time period according to transaction data of the second-hand electronic equipment groups under the transaction channels in the preset time period, determining weights of the respective representative prices according to time differences between the respective dates and the current date, fusing the respective representative prices to obtain channel prices of the second-hand electronic equipment groups under the transaction channels, determining confidence degrees of the channel prices of the second-hand electronic equipment groups under the transaction channels, and determining price attribute values of the second-hand electronic equipment groups according to the channel prices of the second-hand electronic equipment groups under the transaction channels and the confidence degrees of the channel prices of the second-hand electronic equipment groups under the transaction channels. The method can improve the accuracy of determining the price attribute value.

Inventors

GUO CHENGLONG
WU BO

Assignees

深圳市当换网络科技有限公司

Dates

Publication Date: 20260505
Application Date: 20251223

Claims (10)

1. A method for processing data based on second-hand electronic equipment, the method comprising: Determining a second-hand electronic equipment set, and grouping the second-hand electronic equipment in the second-hand electronic equipment set to obtain a plurality of second-hand electronic equipment groups, wherein each second-hand electronic equipment group corresponds to one or more transaction channels; for each transaction channel of each second-hand electronic equipment group, acquiring transaction data of the second-hand electronic equipment group in a preset time period under the transaction channel, and determining respective representative prices of each date of the second-hand electronic equipment group in the preset time period according to the transaction data; Respectively determining weights of the representative prices according to time differences between the dates and the current date; Fusing the representative prices based on the weights of the representative prices to obtain channel prices of the secondhand electronic equipment group under the transaction channel; determining the confidence degree of the channel price under the transaction channel according to the weight of each representative price, wherein the confidence degree is positively correlated with the distribution trend of the weight of each representative price under the transaction channel; and determining the price attribute value of the secondhand electronic equipment group according to the channel price of the secondhand electronic equipment group under each transaction channel and the confidence degree of the channel price under each transaction channel.
2. The method of claim 1, wherein grouping the second-hand electronic devices in the set of second-hand electronic devices results in a plurality of groups of second-hand electronic devices, comprising: Determining brands, models, memories and colors of all second-hand electronic devices in the second-hand electronic device set; and dividing the second-hand electronic equipment with consistent brands, models, memories and colors into a second-hand electronic equipment group.
3. The method of claim 2, wherein the color formation of the second hand electronic devices in the set of second hand electronic devices is determined by a color formation determining step, the color formation passing color formation determining step comprising: Acquiring attribute data and machine condition data of the second-hand electronic equipment aiming at the second-hand electronic equipment set; according to the attribute data and the machine condition data, determining the characteristic data of the second-hand electronic equipment; and inputting the characteristic data into a trained color forming classification model, and outputting the color forming of the second-hand electronic equipment through the color forming classification model.
4. The method of claim 1, wherein said determining, based on the transaction data, a respective representative price for each date of the second hand electronic device group over the preset time period comprises: according to the total data amount of the transaction data in the preset time period, performing Windsor processing on abnormal transaction prices contained in the transaction data to obtain a transaction price data set under the transaction channel; determining the respective transaction quantity of each date; When the transaction quantity is smaller than a preset threshold value, calculating an average value according to the transaction price data corresponding to the date in the transaction price data set to obtain a representative price of the date; and when the transaction quantity is larger than a preset threshold, determining the representative price of the date according to the median of the transaction price data corresponding to the date in the transaction price data set.
5. The method of claim 1, wherein determining the confidence of the channel price under the transaction channel based on the weight of each representative price comprises: calculating a Windsor mean value and a robust scale according to the transaction data; calculating the number of effective samples according to the weight of each representative price; calculating a standard error of a mean value according to the effective sample number and the robust scale; And determining the confidence coefficient of the channel price under the transaction channel according to the standard error of the mean value and the Windsor mean value.
6. The method of claim 5, wherein determining the confidence of the channel price under the transaction channel based on the standard error of the mean and the Windsor mean comprises: calculating the half width of the confidence interval according to the standard error of the mean value; Calculating the width of the relative confidence interval according to the half width of the confidence interval and the Windsor mean value; and determining the confidence degree of the channel price under the transaction channel according to the relative confidence interval width.
7. The method according to any one of claims 1 to 6, further comprising: determining target second-hand electronic equipment to be subjected to price attribute determination; determining a second-hand electronic equipment group to which the target second-hand electronic equipment belongs according to the brand, model, memory and color forming of the target second-hand electronic equipment; and determining the price attribute value of the second-hand electronic equipment group as the price attribute value of the target second-hand electronic equipment.
8. A data processing apparatus based on a second-hand electronic device, the apparatus comprising: The grouping module is used for determining a second-hand electronic equipment set, grouping the second-hand electronic equipment in the second-hand electronic equipment set to obtain a plurality of second-hand electronic equipment groups, wherein each second-hand electronic equipment group corresponds to one or more transaction channels; The representative price determining module is used for acquiring transaction data of the second-hand electronic equipment groups in a preset time period according to each transaction channel of each second-hand electronic equipment group, and determining the respective representative price of each date of the second-hand electronic equipment groups in the preset time period according to the transaction data; The weight determining module is used for determining the weight of each representative price according to the time difference between each date and the current date; The channel price determining module is used for fusing the representative prices based on the weights of the representative prices to obtain channel prices of the secondhand electronic equipment group under the transaction channel; The confidence determining module is used for determining the confidence of the channel price under the transaction channel according to the weight of each representative price, and the confidence is positively correlated with the distribution trend of the weight of each representative price under the transaction channel; And the price attribute value determining module is used for determining the price attribute value of the secondhand electronic equipment group according to the channel price of the secondhand electronic equipment group under each transaction channel and the confidence degree of the channel price of the secondhand electronic equipment group under each transaction channel.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.

Description

Data processing method, device and program product based on second-hand electronic equipment Technical Field The present application relates to the field of computer technologies, and in particular, to a data processing method, apparatus, and program product based on second-hand electronic devices. Background With the development of computer technology, the updating speed of electronic products is increased, and the market scale of second-hand electronic equipment trade is continuously enlarged. In such a large environment, price attribute value determination of secondhand electronic devices becomes an important link. In the related art, a pricing mode based on a machine learning model is adopted, namely brands, models, memories, normal items, flaw items and the like of secondhand electronic equipment are taken as model input data, historical transaction prices are taken as targets to train different regression models, and price prediction is carried out by means of the trained models according to the current mobile phone attribute information. However, the predictive outcome stored in this pricing scheme has hysteresis, which results in a lower accuracy in the final determined price attribute value for the second-hand electronic device. Disclosure of Invention In view of the foregoing, it is desirable to provide a data processing method, apparatus, computer device, computer-readable storage medium, and computer program product based on a secondhand electronic device, which can improve the accuracy of price attribute value determination of the secondhand electronic device. In a first aspect, the present application provides a data processing method based on second-hand electronic equipment, including: Determining a second-hand electronic equipment set, and grouping the second-hand electronic equipment in the second-hand electronic equipment set to obtain a plurality of second-hand electronic equipment groups, wherein each second-hand electronic equipment group corresponds to one or more transaction channels; for each transaction channel of each second-hand electronic equipment group, acquiring transaction data of the second-hand electronic equipment group in a preset time period under the transaction channel, and determining respective representative prices of each date of the second-hand electronic equipment group in the preset time period according to the transaction data; Respectively determining weights of the representative prices according to time differences between the dates and the current date; Fusing the representative prices based on the weights of the representative prices to obtain channel prices of the secondhand electronic equipment group under the transaction channel; determining the confidence degree of the channel price under the transaction channel according to the weight of each representative price, wherein the confidence degree is positively correlated with the distribution trend of the weight of each representative price under the transaction channel; and determining the price attribute value of the secondhand electronic equipment group according to the channel price of the secondhand electronic equipment group under each transaction channel and the confidence degree of the channel price under each transaction channel. In one embodiment, the grouping the second-hand electronic devices in the second-hand electronic device set to obtain a plurality of second-hand electronic device groups includes: Determining brands, models, memories and colors of all second-hand electronic devices in the second-hand electronic device set; and dividing the second-hand electronic equipment with consistent brands, models, memories and colors into a second-hand electronic equipment group. In one embodiment, the color formation of the second hand electronic devices in the set of second hand electronic devices is determined by a color formation determining step, the color formation by color formation determining step comprising: Acquiring attribute data and machine condition data of the second-hand electronic equipment aiming at the second-hand electronic equipment set; according to the attribute data and the machine condition data, determining the characteristic data of the second-hand electronic equipment; and inputting the characteristic data into a trained color forming classification model, and outputting the color forming of the second-hand electronic equipment through the color forming classification model. In one embodiment, the determining, according to the transaction data, the representative prices of the second-hand electronic device group on each date in the preset time period includes: according to the total data amount of the transaction data in the preset time period, performing Windsor processing on abnormal transaction prices contained in the transaction data to obtain a transaction price data set under the transaction channel; determining the respective transaction quantity of each date;