CN-121981745-A - Data pricing method, device and system

CN121981745ACN 121981745 ACN121981745 ACN 121981745ACN-121981745-A

Abstract

The invention discloses a data pricing method, a device and a system, which comprise the steps of obtaining basic data of the same kind, defining a pricing range of target data according to the basic data, pricing the data by referring to the obtained pricing range, pushing the pricing data and displaying the pricing data on a transaction platform. According to the data pricing method, device and system, the pricing range of target data is defined according to basic data, the obtained pricing range is referred to for data pricing, especially in the range of market reference for sellers with insufficient market quotations, the rationality of pricing given by the sellers is guaranteed, the reasonable system of data pricing is matched with the boundary system of data pricing, warning is timely given for the unreasonable pricing, and the trading platform can prompt in time for the continuously low or high price, so that the unreasonable batch situation of market data pricing is avoided.

Inventors

Xiong Shuchu
MENG HAN
ZENG ZHIYONG
ZHANG CHENGQUAN

Assignees

湖南工商大学

Dates

Publication Date: 20260505
Application Date: 20240307

Claims (10)

1. A data pricing method is characterized by comprising the following steps: Step one, obtaining basic data of the same kind, defining a pricing range of target data according to the basic data, pricing data by referring to the obtained pricing range, pushing the pricing data, and displaying on a transaction platform; The target data are specifically data to be priced, wherein the basic data are specifically sales data of a transaction platform; Establishing a boundary system of data pricing, wherein when the data pricing is within the boundary system, the transaction platform takes different measures, marks the adjacent boundary value of continuous data pricing, and prompts the transaction platform; step three, constructing a consumer protection frame, wherein the transaction data is not subjected to pricing modification in a time range, and the time range is disclosed, and the transaction data is subjected to pricing modification outside the time range and is subjected to transaction platform auditing, wherein the minimum value of the time range is 30 days; And step four, summarizing the data pricing quantity of the same user, generating a chart for the summarized data, and displaying the relation between the pricing range and sales volume according to the chart.
2. The method for pricing data according to claim 1, wherein the defining the pricing range of the target data based on the base data in the first step comprises: S1, firstly marking data types, namely marking the data types as H j , j as serial numbers of different types of data, then marking the data pricing amounts of the same type, marking the data pricing amounts as RH j , and sequencing according to the sizes of the data pricing amounts, namely sequentially marking the data pricing amounts as RH 1 、RH 2 、...、RH j , wherein sequencing is carried out randomly when the data pricing amounts are the same; S2, calculating a median of the data pricing amount RH j , marking the median as ZH j , uniformly delineating a basic range to two sides by taking ZH j as a midpoint, and marking the basic range as (ZH k ,ZH s ), wherein the calculation formula is referenced: p is a defined pricing range recommendation value.
3. A data pricing method according to claim 2, wherein the data pricing amount RH j in S2 is calculated as a median, specifically, when j is odd, the median of RH j is marked as Z 1 H j , and when j is even, the median of RH j is marked as Z 2 H j .
4. The method for pricing data according to claim 1, wherein the transaction platform takes different measures when the pricing data in the second step is within and outside the boundary system range, and the specific way of marking the adjacent boundary values for continuous pricing data is as follows: p1, firstly setting the data pricing boundary range, marking as [ PA, PB ], marking real-time data pricing as FH j , when FH j epsilon [ PA, PB ], the data pricing at the moment is normal market pricing, when When the data pricing is abnormal market pricing, further analysis is needed for the abnormal market pricing; p2, setting adjacent boundary points, namely DA and DB in sequence, wherein the range of the low adjacent boundary is [ PA, DA ], the range of the high adjacent boundary is [ DB, PB ], and when more than 70% of the sales data of the user is positioned in [ PA, DA ] or [ DB, PB ], the sales data is marked as too low or too high, and the transaction platform is prompted.
5. The method for pricing data according to claim 4, wherein the specific manner in which the P1 further analysis is required for abnormal market pricing is: And P11, warning the amount of abnormal market pricing by the trading platform, popping up the data pricing boundary range [ PA, PB ] to prompt modification, setting the modification frequency threshold value m, and when the data input by the user is priced m times, still entering the data pricing boundary range [ PA, PB ], wherein the trading platform prohibits the data input.
6. The method for pricing data according to claim 1, wherein in step three, the transaction data is not subject to pricing modification within a time frame, and the time frame is disclosed in the following specific manner: and M1, setting a time threshold T, wherein in the time T, the transaction data pricing changing interface is in an unselected state, and the transaction data processing remark pricing is in an unchangeable time range, and carrying out a formula on the remaining days.
7. The method for pricing data according to claim 1, wherein the specific manner in which the transaction platform audit is performed for pricing modification of the transaction data outside the time frame in step three is as follows: and W1, after the set time range T is exceeded, the transaction data pricing change interface can be selected and data is changed, after the data is changed, the reasons for the remark change are needed, the transaction platform can display after the verification is passed, and the reasons for the remark change are not submitted again after the verification is passed.
8. The method of claim 1, wherein in the fourth step, when the relationship between the pricing range and the sales volume is displayed according to the chart, the relationship between the prices and the sales volume of the products with different attributes can be checked according to the pricing range so as to perform subsequent data pricing adjustment.
9. A data pricing system, comprising: The data pricing module is used for acquiring the basic data of the same type, defining the pricing range of the target data according to the basic data, and pricing the data by referring to the acquired pricing range; the pricing evaluation module is used for establishing a boundary system of data pricing, taking different measures by the transaction platform when the data pricing is respectively within and outside the boundary system range, and marking adjacent boundary values of continuous data pricing; The pricing protection module is used for constructing a consumer protection frame, wherein the transaction data is not subjected to pricing change in a time range, and the transaction data is subjected to pricing change outside the time range and is subjected to transaction platform auditing; And the data summarizing module is used for summarizing the data pricing quantity of the same user, generating a chart for the summarized data, and displaying the relation between the pricing range and sales volume according to the chart.
10. A non-transitory computer readable storage medium containing a computer program which, when executed by a processor, causes the processor to perform the data pricing method of any of claims 1-8.

Description

Data pricing method, device and system Technical Field The invention relates to the technical field of data pricing, in particular to a data pricing method, device and system. Background At present, when a seller sells data on a transaction platform, the seller needs to price the data firstly, although the seller can give out pricing through the evaluation result of the seller to the data, the seller cannot know whether the pricing given by the seller is reasonable or not, especially for sellers with insufficient market quotations, the seller cannot quickly judge the rationality of the pricing given by the data, and for continuously lower or higher prices, the transaction platform cannot prompt in time, the unreasonable condition of batch of the pricing of the market data occurs, and meanwhile, the randomness of the data pricing is changed, the lack of stability and the changed transparency of the transaction data cannot guarantee the rights of consumers and the acceptance of merchants in the market. Disclosure of Invention (One) solving the technical problems Aiming at the defects of the prior art, the invention provides a data pricing method, a data pricing device and a data pricing system, and solves the problems mentioned in the background art. (II) technical scheme In order to achieve the above purpose, the invention is realized by the following technical scheme that the data pricing method specifically comprises the following steps: Step one, obtaining basic data of the same kind, defining a pricing range of target data according to the basic data, pricing data by referring to the obtained pricing range, pushing the pricing data, and displaying on a transaction platform; The target data are specifically data to be priced, wherein the basic data are specifically sales data of a transaction platform; Establishing a boundary system of data pricing, wherein when the data pricing is within the boundary system, the transaction platform takes different measures, marks the adjacent boundary value of continuous data pricing, and prompts the transaction platform; step three, constructing a consumer protection frame, wherein the transaction data is not subjected to pricing modification in a time range, and the time range is disclosed, and the transaction data is subjected to pricing modification outside the time range and is subjected to transaction platform auditing, wherein the minimum value of the time range is 30 days; And step four, summarizing the data pricing quantity of the same user, generating a chart for the summarized data, and displaying the relation between the pricing range and sales volume according to the chart. As an improved technical solution, the specific way of defining the pricing scope of the target data according to the basic data in the first step is as follows: S1, firstly marking data types, namely marking the data types as H j, j as serial numbers of different types of data, then marking the data pricing amounts of the same type, marking the data pricing amounts as RH j, and sequencing according to the sizes of the data pricing amounts, namely sequentially marking the data pricing amounts as RH 1、RH2、...、RHj, wherein sequencing is carried out randomly when the data pricing amounts are the same; S2, calculating a median of the data pricing amount RH j, marking the median as ZH j, uniformly delineating a basic range to two sides by taking ZH j as a midpoint, and marking the basic range as (ZH k,ZHs), wherein the calculation formula is referenced: p is a defined pricing range recommendation value. As an improved technical solution, in S2, when the data pricing amount RH j calculates the median, specifically, when j is an odd number, the median of RH j is marked as Z 1Hj, and when j is an even number, the median of RH j is marked as Z 2Hj. As an improved technical scheme, when the data pricing in the step two is respectively within the boundary system range, the transaction platform takes different measures and marks the adjacent boundary values of the continuous data pricing in the specific modes: p1, firstly setting the data pricing boundary range, marking as [ PA, PB ], marking real-time data pricing as FH j, when FH j epsilon [ PA, PB ], the data pricing at the moment is normal market pricing, when When the data pricing is abnormal market pricing, further analysis is needed for the abnormal market pricing; p2, setting adjacent boundary points, namely DA and DB in sequence, wherein the range of the low adjacent boundary is [ PA, DA ], the range of the high adjacent boundary is [ DB, PB ], and when more than 70% of the sales data of the user is positioned in [ PA, DA ] or [ DB, PB ], the sales data is marked as too low or too high, and the transaction platform is prompted. As an improved technical solution, the specific way in which the situation of the abnormal market pricing in the P1 needs to be further analyzed is as follows: And P11, warning the amount of abnormal market pricing