CN115796869B

CN115796869B - Commodity data processing method and device based on intelligent digital contract

Info

Publication number: CN115796869B
Application number: CN202211481011.7A
Authority: CN
Inventors: 李宁
Original assignee: Yuanjiang Guangzhou Supply Chain Management Partnership LP
Current assignee: Yuanjiang Guangzhou Supply Chain Management Partnership LP
Priority date: 2022-11-24
Filing date: 2022-11-24
Publication date: 2024-01-19
Anticipated expiration: 2042-11-24
Also published as: CN115796869A

Abstract

The invention discloses a commodity data processing method and device based on an intelligent digital contract, wherein the method comprises the following steps: acquiring user information of at least one member user; determining at least one middle-signed user from all the member users based on a drawing algorithm model according to the user information of all the member users; acquiring subscription protocol data of the medium signing user for the target commodity, and generating subscription digital contracts corresponding to the medium signing user according to the subscription protocol data; and receiving buying and selling instructions of the member user aiming at any one of the underwriting digital contracts, and executing contract operation on the underwriting digital contract according to the buying and selling instructions. Therefore, the invention can screen the users entering the field and improve the efficiency and the safety of commodity transaction.

Description

Commodity data processing method and device based on intelligent digital contract

Technical Field

The invention relates to the technical field of data processing, in particular to a commodity data processing method and device based on an intelligent digital contract.

Background

The commodity transaction technology in the prior art still adopts an outdated data processing technology concept, and the convenience of digital contracts and the necessity of user approach screening are not considered. It can be seen that the prior art has defects and needs to be solved.

Disclosure of Invention

The technical problem to be solved by the invention is to provide a commodity data processing method and device based on an intelligent digital contract, which can screen incoming users and improve the efficiency and safety of commodity transaction.

To solve the above technical problems, a first aspect of the present invention discloses a commodity data processing method based on an intelligent digital contract, the method comprising:

acquiring user information of at least one member user;

determining at least one middle-signed user from all the member users based on a drawing algorithm model according to the user information of all the member users;

acquiring subscription protocol data of the medium signing user for the target commodity, and generating subscription digital contracts corresponding to the medium signing user according to the subscription protocol data;

and receiving buying and selling instructions of the member user aiming at any one of the underwriting digital contracts, and executing contract operation on the underwriting digital contract according to the buying and selling instructions.

As an optional implementation manner, in the first aspect of the present invention, before the acquiring subscription agreement data of the endorsed user for the target commodity, the method further includes:

receiving promised payment information and protocol signing information which are sent by the middle sign user and aim at target commodities;

And generating subscription protocol data of the medium sign user for the target commodity according to the promised payment information and the protocol signing information.

In an optional implementation manner, in the first aspect of the present invention, the receiving an order for buying and selling of any one of the underwriting digital contracts by the member user, performing a contract operation on the underwriting digital contract according to the order for buying and selling, includes:

receiving a selling instruction of the middle sign user for the corresponding underwriting digital contract, and freezing the underwriting digital contract and the corresponding target commodity to generate a new frozen digital contract to be stored in a target block chain;

and/or the number of the groups of groups,

and receiving a purchase instruction of the member user aiming at any underwriting digital contract, and executing transaction operation on the underwriting digital contract and the corresponding target commodity to generate a new transaction digital contract and store the new transaction digital contract into the target blockchain.

As an optional implementation manner, in the first aspect of the present invention, after the receiving the selling instruction of the subscription digital contract for the subscription user, the method further includes:

acquiring the underwriting digital contracts corresponding to the plurality of sales instructions, and displaying the underwriting digital contracts corresponding to the plurality of sales instructions on a target transaction platform in a classified manner according to contract information of the underwriting digital contracts; the contract information includes a contract type and/or a contract time;

And/or the number of the groups of groups,

prior to said receiving purchase instructions for any of said underwriting digital contracts by said member users, said method further comprises:

acquiring a purchase contract seeking instruction sent by the member user, freezing currency of the member user corresponding to the purchase contract seeking instruction, generating a new frozen digital contract, and storing the new frozen digital contract into the target blockchain.

As an optional implementation manner, in the first aspect of the present invention, the user information includes at least one of a user category to which the specific member user belongs and user history credit information; and determining at least one middle-signed user from all the member users based on the lottery algorithm model according to the user information of all the member users, wherein the method comprises the following steps:

acquiring preset condition parameters of a lottery algorithm; the lottery algorithm condition parameters comprise at least one of a medium lottery rate, the total number of delivered commodities, a medium lottery rate corresponding to a specific user class or a lottery-free quota;

determining drawing parameters according to the drawing algorithm condition parameters and the user information of all the member users;

and determining at least one middle-sized user from all the member users based on the random lottery algorithm model according to the lottery parameters.

As an optional embodiment, in the first aspect of the invention, the method further comprises:

responding to the inquiry command sent by the member user, acquiring digital contract holding information and/or flow information of the member user, determining an inquiry result and displaying the inquiry result;

and/or the number of the groups of groups,

responding to the statistical instruction sent by the member user, and determining a statistical parameter;

acquiring digital contract holding information and/or running water information of the member users according to the statistical parameters, counting to obtain statistical results, and displaying the statistical results;

and/or the number of the groups of groups,

acquiring a history operation record of any member user;

judging whether the member user has illegal operation or not according to the historical operation record and a preset illegal judgment rule;

if the judgment result is yes, executing punishment operation aiming at the member user; the penalty operation includes at least one of disqualifying the draw, limiting the number of draws, and reclaiming the in-process draw index.

responding to the transfer instruction sent by the member user, and determining transfer request parameters of the member user; the transfer request parameters include at least one of a transfer commodity, a transfer digital contract, a transfer price, a transfer quantity, transfer time information, and a transfer mode;

Executing the transfer operation corresponding to the transfer instruction according to the transfer request parameter;

and/or the number of the groups of groups,

responding to the financing request of the member user, and acquiring financing user information of the member user;

determining at least one recommended product corresponding to the member user from a plurality of preset financing products according to the financing user information

Recommending the recommended products to the member users for selection;

and/or the number of the groups of groups,

responding to a report generation instruction sent by the member user, and acquiring report data aimed at by the report generation instruction; the report data comprises at least one of user credit information and user market information corresponding to the member user;

and generating a user report corresponding to the member user according to the report data.

The second aspect of the invention discloses a commodity data processing device based on intelligent digital contracts, which comprises:

the acquisition module is used for acquiring user information of at least one member user;

the drawing module is used for determining at least one middle-sized drawing user from all the member users based on a drawing algorithm model according to the user information of all the member users;

The generation module is used for acquiring subscription protocol data of the medium signing user for the target commodity and generating subscription digital contracts corresponding to the medium signing user according to the subscription protocol data;

and the operation module is used for receiving the buying and selling instruction of the member user for any one of the underwriting digital contracts and executing contract operation on the underwriting digital contract according to the buying and selling instruction.

As an optional implementation manner, in the second aspect of the present invention, the generating module is further configured to perform the following steps:

As an optional implementation manner, in the second aspect of the present invention, the operation module receives an order of buying and selling for any one of the underwriting digital contracts by the member user, and performs a contract operation on the underwriting digital contract according to the order of buying and selling, including:

And/or the number of the groups of groups,

As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:

the display module is used for acquiring the underwriting digital contracts corresponding to the plurality of the selling instructions and displaying the underwriting digital contracts corresponding to the plurality of the selling instructions on a target transaction platform in a classified manner according to contract information of the underwriting digital contracts; the contract information includes a contract type and/or a contract time;

and/or the number of the groups of groups,

the freezing module is used for acquiring the purchase contract seeking instruction sent by the member user, freezing the currency of the member user corresponding to the purchase contract seeking instruction, generating a new frozen digital contract and storing the new frozen digital contract into the target blockchain.

As an optional implementation manner, in the second aspect of the present invention, the user information includes at least one of a user category to which the specific member user belongs and user history credit information; the drawing module determines a specific mode of at least one middle-signed user from all the member users based on a drawing algorithm model according to the user information of all the member users, and comprises the following steps:

the inquiry module is used for responding to the inquiry instruction sent by the member user, acquiring digital contract holding information and/or flow information of the member user, determining an inquiry result and displaying the inquiry result;

and/or the number of the groups of groups,

the statistics module is used for executing the following steps:

and/or the number of the groups of groups,

the judging module is used for executing the following steps:

Acquiring a history operation record of any member user;

a transfer module for performing the steps of:

and/or the number of the groups of groups,

the recommendation module is used for executing the following steps:

Recommending the recommended products to the member users for selection;

and/or the number of the groups of groups,

the report generating module is used for executing the following steps:

In a third aspect, the present invention discloses another commodity data processing apparatus based on an intelligent digital contract, the apparatus comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform some or all of the steps in the smart digital contract-based commodity data processing method disclosed in the first aspect of the present invention.

A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute some or all of the steps in the commodity data processing method based on a smart digital contract disclosed in the first aspect of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

the embodiment of the invention discloses a commodity data processing method and device based on an intelligent digital contract, wherein the method comprises the following steps: acquiring user information of at least one member user; determining at least one middle-signed user from all the member users based on a drawing algorithm model according to the user information of all the member users; acquiring subscription protocol data of the medium signing user for the target commodity, and generating subscription digital contracts corresponding to the medium signing user according to the subscription protocol data; and receiving buying and selling instructions of the member user aiming at any one of the underwriting digital contracts, and executing contract operation on the underwriting digital contract according to the buying and selling instructions. Therefore, the embodiment of the invention can screen the users entering the field based on the lottery algorithm, and restrict the buying and selling of the commodity through the digital contract technology, so that the users entering the field can be screened, and the efficiency and the safety of commodity transaction are improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of a commodity data processing method based on an intelligent digital contract according to an embodiment of the present invention.

Fig. 2 is a schematic structural diagram of a commodity data processing apparatus based on an intelligent digital contract according to an embodiment of the present invention.

Fig. 3 is a schematic structural diagram of another commodity data processing apparatus based on an intelligent digital contract according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms "second," "second," and the like in the description and in the claims and in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include other steps or elements not expressly listed or inherent to such process, method, article, or device.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses a commodity data processing method and device based on an intelligent digital contract, which can screen incoming users based on a drawing algorithm and restrict buying and selling of commodities through a digital contract technology, so that the incoming users can be screened, and the commodity transaction efficiency and safety are improved. The following will describe in detail.

Example 1

Referring to fig. 1, fig. 1 is a flow chart of a commodity data processing method based on an intelligent digital contract according to an embodiment of the present invention. The commodity data processing method based on the intelligent digital contract described in fig. 1 is applied to a data processing chip, a processing terminal or a processing server (wherein the processing server can be a local server or a cloud server). As shown in fig. 1, the smart digital contract-based commodity data processing method may include the operations of:

101. User information of at least one member user is acquired.

Alternatively, the member user may be a user who wants to conduct commodity transaction, and may become a member by means of pre-registration.

Optionally, the member user may enter the cloud platform through a mobile phone terminal, a VR device or a holographic projection to perform commodity transaction, and the manner of outputting the transaction operation or the transaction instruction may also be through a VR interaction device, a keyboard mouse, a motion capture device, and the like.

102. And determining at least one middle-signed user from all the member users based on the lottery algorithm model according to the user information of all the member users.

In the specific implementation scenario, in the time limit of the drawing issued by the cloud platform, after the member signs in the drawing, the member signs a subscription agreement on line on the cloud platform, signs and accepts the payment to the cloud platform, so that the payment due is paid to the cloud platform in full on the same day after the commodity is received in a week, and the member without the payment can opt to exit or leave the cloud platform.

103. And acquiring subscription protocol data of the middle sign user for the target commodity, and generating subscription digital contracts corresponding to the middle sign user according to the subscription protocol data.

In the specific implementation scenario, the member user can choose to generate a digital contract (SGR-special offer right or license for short) with the signed commodity subscription agreement, and the generated digital contract contains all relevant information of the commodity subscribed by the member and stores the information into the blockchain, and can carry out the order-hanging transaction at the compliant agricultural product transaction center.

104. And receiving buying and selling instructions of the member user aiming at any underwriting digital contract, and executing contract operation on the underwriting digital contract according to the buying and selling instructions.

In the specific implementation scenario, the member may place the acquired digital contract on the statement at the qualified agricultural product transaction center, issue the digital contract sales information, and the qualified agricultural product transaction center freezes the digital contract on which the statement is placed (freezes the commodity corresponding to the digital contract at the same time), so as to generate a new digital contract and store the new digital contract in the blockchain.

In the specific implementation scenario, the member can issue related purchasing information at the compliant agricultural product transaction center according to the self demand to perform purchasing of the digital contract, and meanwhile, the compliant agricultural product transaction center freezes wallet currency for purchasing the digital contract transaction at the time to generate a new digital contract and store the new digital contract into the blockchain.

In particular, the member/user should be independently charged with business and legal risks for the "sell" and "buy" information that is published on the platform by the member/user.

In the specific implementation scenario, the digital contract information of the current ordering transaction is displayed in a centralized manner by the compliant agricultural product transaction center, and is displayed in a classified manner according to different types and time of the digital contract, so that the member can select to check the digital contract information of the compliant agricultural product transaction center, and the buying and selling transaction of the digital contract can be performed by the compliant agricultural product transaction center.

In the specific implementation scenario, the member can check the digital contract condition held in the compliant agricultural product transaction center account, can carry out order-hanging sales or digital contract purchasing on the digital contract held by the member, and can carry out query statistics on the digital contract running condition in the compliant agricultural product transaction center account.

Therefore, the embodiment of the invention can screen the users entering the field based on the lottery algorithm, and restrict the buying and selling of the commodities through the digital contract technology, so that the users entering the field can be screened, and the efficiency and the safety of commodity transaction are improved. Furthermore, the cloud platform in the implementation further digitizes expected orders of consumers and producers through intelligent contracts, reversely drives each supply and demand link of interconnected value consumption circulation, and trace back and lock the distribution principle between each production element and benefit chain, thereby forming a decentralised special extraction interest, leading the consumers, namely creators, and being capable of guaranteeing the investment and income of the consumers and the food edible safety.

As an optional implementation manner, before acquiring subscription agreement data of the target commodity by the endorsement user in the step, the method further includes:

Receiving promised payment information and protocol signing information which are sent by a middle sign user and aim at target commodities;

and generating subscription agreement data of the medium signing user aiming at the target commodity according to the promised payment information and the agreement signing information.

Optionally, generating subscription agreement data of the middle sign user for the target commodity according to the promised payment information and the agreement signing information includes:

acquiring historical commitment information of a middle sign user; the historical promise information comprises at least one of historical credit information, historical payment information and historical contract information;

according to the historical promise information, determining historical promise information of a user and corresponding promise scene characteristics; the characteristics of the default scene are used for indicating promise characteristics, transaction characteristics or commodity characteristics in the default scene corresponding to the history default information of the user;

calculating feature similarity between the feature of the default scene and the feature of the scene corresponding to the protocol signing information, judging whether the feature similarity is larger than a preset feature similarity threshold, and if so, refusing to generate subscription protocol data of the medium-subscription user;

if not, generating subscription agreement data of the middle sign user aiming at the target commodity according to the promised payment information and the agreement signing information.

Specifically, a plurality of history violations of the user and contract types corresponding to each history violation can be obtained, and the similarity between the contract types and the contract type of the current signed agreement is calculated to obtain the characteristic similarity.

By the implementation mode, the security of protocol signing can be improved, and pollution of a user losing confidence to the whole commodity transaction system or system is avoided.

As an optional embodiment, in the step, receiving an order of buying and selling for any subscription digital contract by the member user, performing a contract operation for the subscription digital contract according to the order of buying and selling, including:

receiving a selling instruction of a middle sign user aiming at a corresponding underwriting digital contract, and freezing the underwriting digital contract and a corresponding target commodity to generate a new frozen digital contract to be stored in a target blockchain;

and/or the number of the groups of groups,

and receiving a purchase instruction of a member user aiming at any underwriting digital contract, and executing transaction operation on the underwriting digital contract and the corresponding target commodity to generate a new transaction digital contract to be stored in the target blockchain.

Optionally, the method may further include:

acquiring a plurality of selling instructions and purchasing instructions of any member user in a historical time period;

Determining the instruction initiating times and a plurality of instruction initiating objects of the member user in the historical time period according to the plurality of selling instructions and purchasing instructions;

calculating the repeatability among a plurality of instruction initiating objects, and judging whether the repeatability is larger than a preset repeatability threshold value or not and whether the instruction initiating times are larger than a preset times threshold value or not;

if the judgment result is yes, determining the member user as an abnormal user, and limiting the subsequent contract operation of the member user.

Through the embodiment, commodity transaction based on the digital contract technology and the blockchain technology can be realized, meanwhile, the security of the transaction can be improved, and malicious operation of malicious users is prevented.

As an optional implementation manner, in the step, after receiving the selling instruction of the underwriting user for the corresponding underwriting digital contract, the method further includes:

acquiring underwriting digital contracts corresponding to the plurality of selling instructions, and displaying the underwriting digital contracts corresponding to the plurality of selling instructions on the target transaction platform in a classified manner according to contract information of the underwriting digital contracts.

Optionally, the contract information includes a contract type and/or a contract time.

Optionally, according to contract information of the subscription digital contracts, classifying and displaying the subscription digital contracts corresponding to the plurality of sales instructions on the target transaction platform, including:

According to contract information of the underwriting digital contracts, based on a clustering algorithm, dividing underwriting digital contracts corresponding to a plurality of selling instructions into a plurality of contract groups; contract information of each contract group is the same or similar;

acquiring contract information of all contracts in each contract group and processing the contract information into information data with the same dimension;

inputting information data of all contract groups into a pre-trained sequencing neural network model to obtain display priority orders corresponding to all contract groups; the sorting neural network model comprises a single-hot algorithm model for data conversion, a contract purchase probability prediction neural network model and a hidden Markov chain algorithm model; the contract purchase probability prediction neural network model is used for predicting the purchase probability of any contract group according to the information data of the contract group; the hidden Markov chain algorithm model calculates a contract group display sequence with highest probability according to the purchased probabilities and information data of all contract groups.

Through the implementation mode, classified display of the subscription digital contracts on the target transaction platform can be achieved, and the display effect is improved.

As an alternative embodiment, before receiving the purchase instruction of the member user for any underwriting digital contract, the method further comprises:

Acquiring a purchase contract seeking instruction sent by a member user, freezing currency of the member user corresponding to the purchase contract seeking instruction, generating a new frozen digital contract, and storing the new frozen digital contract into a target block chain.

As an optional implementation manner, in the step, the user information includes at least one of a user category to which the specific member user belongs and user history credit information; according to the user information of all the member users, determining at least one middle-sized user from all the member users based on the lottery algorithm model, wherein the method comprises the following steps:

determining drawing parameters according to the drawing algorithm condition parameters and the user information of all member users;

and determining at least one middle-sized lottery user from all the member users based on the random lottery algorithm model according to the lottery parameters.

Specifically, the drawing rate and the throwing ratio in the drawing can be set and automatically matched according to the number of people participating in the drawing and the production capacity of the product, and the throwing quota can be allocated.

Optionally, different middle-rate or no-draw processes, and different quota ratios may be set for a particular group.

In particular, the goods of the invention include, but are not limited to, livestock, seafood and other agricultural and sideline products, industrial products, and production materials in different areas.

Specifically, in the case that the commodity is a polar pig, each drawing subject only has 200 indexes per drawing. The pumping is completed. Regional partners (agents) must organize the number of raffles in proportion, and the number of raffles is insufficient and does not enjoy the regional proportion index. The number of people not in place according to the lottery proportion is regarded as automatically giving up the lottery qualification. Specifically, during drawing, the system will display the proportion of the middle drawing, the year, month and day of delivery. The system displays detailed information such as the sex, the native place, the age, the address, the contact information and the like of the receiver. The background will display all details of the drawstring including reputation name, work level, time to enter and leave, job, education level, specialties.

Through the embodiment, more reasonable and effective drawing can be realized, and more fair user screening and user competition are realized.

As an alternative embodiment, the method further comprises:

and responding to the inquiry command sent by the member user, acquiring digital contract holding information and/or stream information of the member user, determining an inquiry result and displaying the inquiry result.

As an alternative embodiment, the method further comprises:

responding to a statistical instruction sent by a member user, and determining a statistical parameter;

acquiring digital contract holding information and/or flow information of member users according to the statistical parameters, counting to obtain statistical results, and displaying the statistical results;

as an alternative embodiment, the method further comprises:

acquiring a history operation record of any member user;

and if the judgment result is yes, executing the punishment operation aiming at the member user.

Specifically, the penalty operation includes at least one of disqualifying the drawing, limiting the number of draws, and retrieving the in-process drawing index.

Optionally, determining whether the member user has the violation operation according to the history operation record and a preset violation determination rule includes:

inputting the historical operation record of the member user into a trained violation judgment neural network model to obtain a judgment result output by the model; the violation judging neural network model is obtained through training a training set comprising a plurality of training operation records and corresponding labels of whether violations exist or not;

And judging whether the member user has illegal operation or not according to the judging result.

As an alternative embodiment, the method further comprises:

responding to a transfer instruction sent by a member user, and determining a transfer request parameter of the member user; the transfer request parameters include at least one of a transfer commodity, a transfer digital contract, a transfer price, a transfer quantity, transfer time information, and a transfer mode;

and executing the transfer operation corresponding to the transfer instruction according to the transfer request parameter.

In particular, there may be provided paid or gratuitous transfers, even gifts, and prices, amounts and delivery dates of transfers when ownership is transferred. It can be transferred in batches or at one time.

As an alternative embodiment, the method further comprises:

The recommended products are recommended to the member users for selection.

Alternatively, the financing service may provide different financial products for a variety of different financial institutions.

Specifically, the financing request of the member user must not be separated from the subscription order and digital contract content, and at the same time, the financing entity needs to independently assume legal responsibility for the financial institution.

As an alternative embodiment, the method further comprises:

responding to a report generation instruction sent by a member user, and acquiring report data aimed at by the report generation instruction; the report data comprises at least one of user credit information and user market information corresponding to the member users;

Example two

Referring to fig. 2, fig. 2 is a schematic structural diagram of a commodity data processing apparatus based on an intelligent digital contract according to an embodiment of the present invention. The commodity data processing apparatus based on the intelligent digital contract described in fig. 2 is applied to a data processing chip, a processing terminal or a processing server (wherein the processing server may be a local server or a cloud server). As shown in fig. 2, the smart digital contract-based commodity data processing apparatus may include:

an acquisition module 201, configured to acquire user information of at least one member user.

The drawing module 202 is configured to determine at least one middle-sized drawing user from all member users based on the drawing algorithm model according to the user information of all member users.

The generating module 203 is configured to obtain subscription agreement data of the middle-sign user for the target commodity, and generate a subscription digital contract corresponding to the middle-sign user according to the subscription agreement data.

And the operation module 204 is used for receiving the buying and selling instruction of the member user for any underwriting digital contract and executing the contract operation on the underwriting digital contract according to the buying and selling instruction.

As an alternative embodiment, the generating module 203 is further configured to perform the following steps:

As an alternative embodiment, the operation module 204 receives a buy-sell instruction for any subscription digital contract of the member user, and performs a contract operation on the subscription digital contract according to the buy-sell instruction, including:

and/or the number of the groups of groups,

Optionally, the operation module 204 may further perform the following steps:

As an alternative embodiment, the apparatus further comprises:

the display module is used for acquiring the underwriting digital contracts corresponding to the plurality of selling instructions, and displaying the underwriting digital contracts corresponding to the plurality of selling instructions on the target transaction platform in a classified mode according to the contract information of the underwriting digital contracts.

As an alternative embodiment, the apparatus further comprises:

the freezing module is used for acquiring the purchase contract seeking instruction sent by the member user, freezing the currency of the member user corresponding to the purchase contract seeking instruction, generating a new frozen digital contract and storing the new frozen digital contract in the target block chain.

As an optional implementation manner, the user information includes at least one of a user category to which the specific member user belongs and user history credit information; the drawing module determines a specific mode of at least one middle drawing user from all member users based on a drawing algorithm model according to the user information of all member users, and comprises the following steps:

As an alternative embodiment, the apparatus further comprises:

and the query module is used for responding to the query instruction sent by the member user, acquiring the digital contract holding information and/or the flow information of the member user, determining the query result and displaying the query result.

As an alternative embodiment, the apparatus further comprises:

the statistics module is used for executing the following steps:

and acquiring digital contract holding information and/or flow information of the member users according to the statistical parameters, counting to obtain statistical results, and displaying the statistical results.

As an alternative embodiment, the apparatus further comprises:

the judging module is used for executing the following steps:

acquiring a history operation record of any member user;

As an alternative embodiment, the apparatus further comprises:

a transfer module for performing the steps of:

As an alternative embodiment, the apparatus further comprises:

the recommendation module is used for executing the following steps:

The recommended products are recommended to the member users for selection.

As an alternative embodiment, the apparatus further comprises:

the report generating module is used for executing the following steps:

Example III

Referring to fig. 3, fig. 3 is a schematic diagram illustrating another commodity data processing apparatus according to an embodiment of the present invention. The commodity data processing apparatus based on intelligent digital contract described in fig. 3 is applied to a data processing chip, a processing terminal or a processing server (wherein the processing server may be a local server or a cloud server). As shown in fig. 3, the smart digital contract-based commodity data processing apparatus may include:

A memory 301 storing executable program code;

a processor 302 coupled with the memory 301;

wherein the processor 302 invokes executable program code stored in the memory 301 for performing the steps of the smart digital contract-based commodity data processing method described in embodiment one.

Example IV

The embodiment of the invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps of the commodity data processing method based on intelligent digital contract described in the embodiment.

Example five

The present invention discloses a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform the steps of the commodity data processing method based on a smart digital contract described in the embodiment.

The foregoing describes certain embodiments of the present disclosure, other embodiments being within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. Furthermore, the processes depicted in the accompanying drawings do not necessarily have to be in the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-transitory computer readable storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to portions of the description of method embodiments being relevant.

The apparatus, the device, the nonvolatile computer readable storage medium and the method provided in the embodiments of the present disclosure correspond to each other, and therefore, the apparatus, the device, and the nonvolatile computer storage medium also have similar advantageous technical effects as those of the corresponding method, and since the advantageous technical effects of the method have been described in detail above, the advantageous technical effects of the corresponding apparatus, device, and nonvolatile computer storage medium are not described herein again.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., a field programmable gate array (Field Programmable gate array, FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware DescriptionLanguage), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (RubyHardware Description Language), etc., VHDL (Very-High-SpeedIntegrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.

It will be appreciated by those skilled in the art that the present description may be provided as a method, system, or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description embodiments may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

Finally, it should be noted that: the embodiment of the invention discloses a commodity data processing method and device based on intelligent digital contracts, which are disclosed by the embodiment of the invention only and are used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. A commodity data processing method based on intelligent digital contracts, the method comprising:

Acquiring user information of at least one member user;

receiving buying and selling instructions of the member user aiming at any one of the underwriting digital contracts, and executing contract operation on the underwriting digital contract according to the buying and selling instructions;

before the acquiring the subscription protocol data of the medium-sign user for the target commodity, the method further comprises the following steps:

generating subscription protocol data of the medium sign user for the target commodity according to the promised payment information and the protocol signing information; the history commitment information of the middle sign user is obtained; according to the historical promise information, determining historical default information and corresponding default scene characteristics of the middle-signed user; calculating the feature similarity between the feature of the default scene and the feature of the scene corresponding to the protocol signing information, and judging whether the feature similarity is larger than a preset feature similarity threshold; if yes, refusing to generate subscription protocol data of the medium-subscription user; if not, generating subscription protocol data of the medium signing user aiming at the target commodity according to the promised payment information and the protocol signing information;

The receiving the buying and selling instruction of the member user for any one of the underwriting digital contracts, executing the contract operation on the underwriting digital contract according to the buying and selling instruction, and comprising the following steps:

and/or the number of the groups of groups,

receiving a purchase instruction of the member user aiming at any subscription digital contract, and executing transaction operation on the subscription digital contract and the corresponding target commodity to generate a new transaction digital contract to store in the target blockchain;

after said receiving the sales instructions for the underwriting digital contracts for which the underwriting users correspond, the method further comprises:

acquiring the underwriting digital contracts corresponding to the plurality of sales instructions, and displaying the underwriting digital contracts corresponding to the plurality of sales instructions on a target transaction platform in a classified manner according to contract information of the underwriting digital contracts; the contract information includes a contract type and/or a contract time; the method comprises the steps of dividing the underwriting digital contracts corresponding to a plurality of selling instructions into a plurality of contract groups based on a clustering algorithm according to contract information of the underwriting digital contracts, wherein the contract information of each contract group is the same or similar; acquiring contract information of all contracts in each contract group and processing the contract information into information data with the same dimension; inputting information data of all contract groups into a pre-trained sequencing neural network model to obtain display priority orders corresponding to all contract groups;

And/or the number of the groups of groups,

2. The smart digital contract-based commodity data processing method according to claim 1, wherein the user information includes at least one of a user category to which a specific member user belongs, and user history credit information; and determining at least one middle-signed user from all the member users based on the lottery algorithm model according to the user information of all the member users, wherein the method comprises the following steps:

3. The smart digital contract-based commodity data processing method according to claim 1, further comprising:

and/or the number of the groups of groups,

acquiring a history operation record of any member user;

4. The smart digital contract-based commodity data processing method according to claim 1, further comprising:

and/or the number of the groups of groups,

determining at least one recommended product corresponding to the member user from a plurality of preset financing products according to the financing user information;

recommending the recommended products to the member users for selection;

and/or the number of the groups of groups,

5. A commodity data processing apparatus based on an intelligent digital contract, the apparatus comprising:

the operation module is used for receiving the buying and selling instruction of the member user for any one of the underwriting digital contracts and executing contract operation on the underwriting digital contract according to the buying and selling instruction;

the generation module is further configured to perform the following steps:

The operation module receives the buying and selling instruction of the member user for any one of the underwriting digital contracts, and executes the contract operation of the underwriting digital contract according to the buying and selling instruction in a specific mode, which comprises the following steps:

and/or the number of the groups of groups,

the apparatus further comprises:

the display module is used for acquiring the underwriting digital contracts corresponding to the plurality of the selling instructions and displaying the underwriting digital contracts corresponding to the plurality of the selling instructions on a target transaction platform in a classified manner according to contract information of the underwriting digital contracts; the contract information includes a contract type and/or a contract time; the method comprises the steps of dividing the underwriting digital contracts corresponding to a plurality of selling instructions into a plurality of contract groups based on a clustering algorithm according to contract information of the underwriting digital contracts, wherein the contract information of each contract group is the same or similar; acquiring contract information of all contracts in each contract group and processing the contract information into information data with the same dimension; inputting information data of all contract groups into a pre-trained sequencing neural network model to obtain display priority orders corresponding to all contract groups;

6. A commodity data processing apparatus based on an intelligent digital contract, the apparatus comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform the smart digital contract-based commodity data processing method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that it stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the commodity data processing method according to any one of claims 1 to 4 based on a smart digital contract.