Data processing method and device based on block chain, storage medium and electronic equipment

Abstract

The invention discloses a data processing method and device based on a block chain, a storage medium and electronic equipment. Relates to the technical field of block chains, and the method comprises the steps that historical donation information of a target object is acquired through a donation registration node in a block chain, and the historical donation information at least comprises attribute information, donation project information, donation time information and donation amount information of the target object; processing the historical donation information through an analysis node in the block chain to obtain a target knowledge graph corresponding to the target object; and scoring the target object based on the target knowledge graph through the evaluation node in the block chain to obtain a target score value, and determining a handling strategy of the to-be-handled loan service of the target object based on the target score value. Through the method and the device, the problem of poor matching effect caused by matching a corresponding service strategy for the loan service to be handled by the user according to the historical transaction data of the user in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and more specifically, to a blockchain-based data processing method and device, storage medium, and electronic device. Background Art

[0002] With the continuous development of the economy, the emergence of loan services has brought convenience to those in urgent need of funds. Financial institutions that provide loan services often match corresponding business strategies for users' pending loans based on their historical transaction data, such as loan amount, loan issuance method, and loan management strategy. However, this approach suffers from poor matching results.

[0003] Currently, no effective solution has been proposed to the problem that in related technologies, a corresponding business strategy is matched for a user's pending loan business based on the user's historical transaction data, resulting in poor matching results. Summary of the Invention

[0004] The main purpose of this application is to provide a blockchain-based data processing method and device, storage medium and electronic device to solve the problem in related technologies of matching corresponding business strategies for a user's pending loan business based on the user's historical transaction data, resulting in poor matching results.

[0005] To achieve the above objectives, according to one aspect of the present application, a blockchain-based data processing method is provided. The method comprises: obtaining historical donation information of a target subject through a donation registration node in a blockchain, wherein the historical donation information includes at least: attribute information of the target subject, donation project information, donation time information, and donation amount information; processing the historical donation information through an analysis node in the blockchain to obtain a target knowledge graph corresponding to the target subject; scoring the target subject based on the target knowledge graph through an evaluation node in the blockchain to obtain a target score value; and determining a processing strategy for a loan business to be processed for the target subject based on the target score value, wherein the loan business is processed for the target subject according to the processing strategy.

[0006] Furthermore, the historical donation information is processed by the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object, including: obtaining historical hot events within the historical time period corresponding to the historical donation information; pre-processing the historical hot events and the historical donation information to obtain processed data information; and constructing the target knowledge graph of the target object based on the processed data information.

[0007] Furthermore, constructing the target knowledge graph of the target object based on the processed data information includes: performing entity recognition on the processed data information to obtain multiple entities; determining the entity relationships between the multiple entities based on the processed data information; and constructing the target knowledge graph based on the multiple entities and the entity relationships.

[0008] Furthermore, scoring the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain the target scoring value includes: analyzing the target knowledge graph to obtain the donation portrait of the target object; and scoring the target object based on the donation portrait to obtain the target scoring value.

[0009] Furthermore, the target knowledge graph is analyzed to obtain a donation portrait of the target object, including: obtaining a donation time feature value based on the time span information in the target knowledge graph; obtaining a donation frequency feature value based on the number of donations information in the target knowledge graph; obtaining a donation amount feature value based on the donation amount information in the target knowledge graph; obtaining a donation tendency feature value based on the donation project information in the target knowledge graph and the historical hot events; and obtaining a donation portrait of the target object based on the donation time feature value, the donation frequency feature value, the donation amount feature value and the donation tendency feature value.

[0010] Furthermore, obtaining the donation tendency feature value based on the donation project information and the historical hot events in the target knowledge graph includes: classifying the donation tendency of the target object based on the donation project information and the historical hot events through a decision tree to obtain a first donation tendency item; processing the donation project information and the historical hot events through a support vector machine to obtain a second donation tendency item; and obtaining the donation tendency feature value based on the first donation tendency item and the second donation tendency item.

[0011] Furthermore, after the target object is scored based on the target knowledge graph by the evaluation node in the blockchain to obtain a target score value, the method also includes: determining a target digital collection based on the target score value; and performing consensus processing on the target digital collection in the blockchain, wherein the target digital collection is used by the target object to conduct business with a third party partner.

[0012] To achieve the above-mentioned objectives, according to another aspect of the present application, a blockchain-based data processing device is provided. The device comprises: an acquisition unit configured to acquire historical donation information of a target object through a donation registration node in a blockchain, wherein the historical donation information includes at least attribute information of the target object, donation project information, donation time information, and donation amount information; a processing unit configured to process the historical donation information through an analysis node in the blockchain to obtain a target knowledge graph corresponding to the target object; and a scoring unit configured to score the target object based on the target knowledge graph through an evaluation node in the blockchain to obtain a target score value, and to determine a processing strategy for a loan business to be processed by the target object based on the target score value, wherein the loan business is processed for the target object according to the processing strategy.

[0013] Furthermore, the processing unit includes: an acquisition sub-unit, used to obtain historical hot events within the historical time period corresponding to the historical donation information; a processing sub-unit, used to pre-process the historical hot events and the historical donation information to obtain processed data information; and a construction sub-unit, used to construct the target knowledge graph of the target object based on the processed data information.

[0014] Furthermore, the construction subunit includes: an identification module for performing entity recognition on the processed data information to obtain multiple entities; a first determination module for determining the entity relationship between the multiple entities based on the processed data information; and a construction module for constructing the target knowledge graph based on the multiple entities and the entity relationship.

[0015] Furthermore, the scoring unit includes: an analysis subunit, used to analyze the target knowledge graph to obtain a donation portrait of the target object; and a scoring subunit, used to score the target object based on the donation portrait to obtain the target scoring value.

[0016] Furthermore, the analysis subunit includes: a first processing module, used to obtain a donation time feature value based on the time span information in the target knowledge graph; a second processing module, used to obtain a donation frequency feature value based on the number of donations information in the target knowledge graph; a third processing module, used to obtain a donation amount feature value based on the donation amount information in the target knowledge graph; a fourth processing module, used to obtain a donation tendency feature value based on the donation project information in the target knowledge graph and the historical hot events; a second determination module, used to obtain a donation portrait of the target object based on the donation time feature value, the donation frequency feature value, the donation amount feature value and the donation tendency feature value.

[0017] Furthermore, the fourth processing module includes: a classification submodule, which is used to classify the donation tendency of the target object based on the donation project information and the historical hot events through a decision tree to obtain a first donation tendency item; a processing submodule, which is used to process the donation project information and the historical hot events through a support vector machine to obtain a second donation tendency item; and a determination submodule, which is used to obtain the donation tendency feature value based on the first donation tendency item and the second donation tendency item.

[0018] Furthermore, the device also includes: a determination unit, which is used to score the target object based on the target knowledge graph through the evaluation node in the blockchain, and after obtaining the target score value, determine the target digital collection based on the target score value; a consensus unit, which is used to perform consensus processing on the target digital collection in the blockchain, wherein the target digital collection is used by the target object to conduct business with a third party.

[0019] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is run, the device where the storage medium is located is controlled to execute any one of the above-mentioned blockchain-based data processing methods.

[0020] According to another aspect of an embodiment of the present invention, an electronic device is provided, comprising a memory storing an executable program; and a processor for running the program, wherein the program executes any one of the above-described blockchain-based data processing methods when running.

[0021] In an embodiment of the present application, historical donation information of a target object is obtained through a donation registration node in a blockchain, wherein the historical donation information includes at least: attribute information of the target object, donation project information, donation time information, and donation amount information; the historical donation information is processed through an analysis node in a blockchain to obtain a target knowledge graph corresponding to the target object; the target object is scored based on the target knowledge graph by an evaluation node in a blockchain to obtain a target score value, and based on the target score value, a processing strategy for a loan business to be processed by the target object is determined, wherein, according to the processing strategy, a target knowledge graph corresponding to the target object is constructed through an analysis node in a blockchain, and the evaluation node scores the target object based on the target knowledge graph to determine the processing strategy for the loan business, thereby achieving the purpose of more accurately matching the processing strategy for the loan business, and matching the corresponding loan business strategy through donation information can also achieve the technical effect of stimulating the development of charitable business, thereby solving the technical problem in the related art of matching the corresponding business strategy for the user's pending loan business based on the user's historical transaction data, resulting in poor matching effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0023] Figure 1 This is a hardware structure block diagram of a computer terminal provided according to an embodiment of the present application;

[0024] Figure 2 This is the process of the data processing method based on blockchain provided by the embodiment of this application Figure 1 ;

[0025] Figure 3 is a schematic diagram of a target knowledge graph provided according to an embodiment of the present application;

[0026] Figure 4 This is the process of the data processing method based on blockchain provided by the embodiment of this application Figure 2 ;

[0027] Figure 5 This is the process of the data processing method based on blockchain provided by the embodiment of this application Figure 3 ;

[0028] Figure 6 This is a schematic diagram of a blockchain provided according to an embodiment of the present application;

[0029] Figure 7 is a schematic diagram of a blockchain-based data processing device provided according to an embodiment of the present application;

[0030] Figure 8 This is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] It should be noted that the collected information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation portals for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or institutions to provide users with corresponding operation portals for users to choose to agree or refuse the automated decision-making results; if the user chooses to refuse, the expert decision-making process will be entered.

[0034] Example 1

[0035] According to an embodiment of the present application, an embodiment of a method for blockchain-based data processing is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The following is a hardware block diagram of a computer terminal (or mobile device) for implementing a data processing method based on blockchain. Figure 1As shown, the computer terminal 10 (or mobile device) may include one or more (illustrated as 102a, 102b, ..., 102n in the figure) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0037] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0038] Memory 104 can be used to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the blockchain-based data processing method in the embodiments of the present application. Processor 102 executes the software programs and modules stored in memory 104 to perform various functional applications and data processing, thereby implementing the aforementioned blockchain-based data processing method. Memory 104 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory located remotely from processor 102, which can be connected to computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0039] The transmission device 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0040] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0041] Under the above operating environment, this application provides Figure 2 The blockchain-based data processing method shown. Figure 2 This is the process of the data processing method based on blockchain according to the first embodiment of this application Figure 1 The method comprises:

[0042] Step S201: Obtain historical donation information of the target object through the donation registration node in the blockchain, wherein the historical donation information at least includes: attribute information of the target object, donation project information, donation time information and donation amount information.

[0043] Alternatively, the public disclosure and promotion of individual donations in existing technologies is relatively fragmented. Therefore, in this embodiment, a blockchain database cloud storage function is used to provide charitable organizations with registered user donation records. This means that historical donation information for the target recipients is obtained through the donation registration node in the blockchain. The donation registration node leverages the decentralized nature of blockchain technology to ensure public and transparent records of customer charitable donations. Historical donation information includes, but is not limited to, customer name, donation project, donation amount, donated items and quantity, donation date, recipient organization, and organization code.

[0044] Step S202: Process the historical donation information through the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object.

[0045] Optionally, historical donation information is cleaned, analyzed, and integrated through analysis nodes in the blockchain, and the donor-centered relationship graph information is continuously improved to obtain the target knowledge graph corresponding to the target object mentioned above.

[0046] In step S203, the target object is scored based on the target knowledge graph through the evaluation node in the blockchain to obtain a target score value, and based on the target score value, a processing strategy for the target object's loan business to be processed is determined, wherein the loan business is processed for the target object according to the processing strategy.

[0047] Optionally, after obtaining the above-mentioned target knowledge graph, the target object is scored based on the target knowledge graph through the evaluation node in the blockchain. For example, an expert strategy model can be set on the evaluation node, and the target knowledge graph is scored by the expert strategy model to obtain the above-mentioned target score value. Finally, according to the target score value, the processing strategy of the target object's loan business to be processed is determined. For example, different target score values ​​can correspond to different loan amounts, different loan issuance times, different loan interest rates and other processing strategies.

[0048] To sum up, by constructing the target knowledge graph corresponding to the target object through historical donation information, and the evaluation node scoring the target object based on the target knowledge graph to determine the loan business processing strategy, the purpose of more accurately matching the loan business processing strategy is achieved. In addition, by matching the corresponding loan business strategy through donation information, the technical effect of stimulating the development of charitable business can also be achieved.

[0049] Optionally, in the blockchain-based data processing method provided in the embodiment of the present application, historical donation information is processed through the analysis node in the blockchain to obtain a target knowledge graph corresponding to the target object, including: obtaining historical hot events within the historical time period corresponding to the historical donation information; pre-processing the historical hot events and historical donation information to obtain processed data information; and constructing a target knowledge graph of the target object based on the processed data information.

[0050] In an optional embodiment, the following steps are used to obtain a target knowledge graph for the target object: RPA is used to crawl a portal website to collate and collect social charity hot topics, specifically, to obtain historical hot topics within the historical time period corresponding to historical donation information. Analysis nodes are then used to preprocess the historical hot topics and donation information, for example, by filtering and cleaning invalid and duplicate data. Finally, a target knowledge graph for the target object is constructed based on this processed data.

[0051] For example, key entities such as people, donation projects, donation amounts, etc. are extracted from the processed historical donation information, and then the semantic relationships between two or more entities are extracted from the processed historical donation information. Finally, a relationship knowledge graph with the donor (that is, the target object mentioned above) as the center is constructed: name, donation organization, donation project, donated items, donation amount, and corresponding historical hot events.

[0052] By constructing a target knowledge graph corresponding to the user's donation information, complex data relationships can be displayed in a graphical manner, which facilitates the analysis and evaluation of the user's donation behavior, and then matches the user with a more suitable loan processing strategy.

[0053] Optionally, in the blockchain-based data processing method provided in an embodiment of the present application, constructing a target knowledge graph of a target object based on the processed data information includes: performing entity recognition on the processed data information to obtain multiple entities; determining entity relationships between multiple entities based on the processed data information; and constructing a target knowledge graph based on the multiple entities and entity relationships.

[0054] In an optional embodiment, the following steps are used to obtain the target knowledge graph of the target object: first, entity recognition is performed on the processed data information to obtain multiple entities, such as user name, user ID number, bank card number, mobile phone number, third-party payment account, charity organization, charity project, and social hot spot. Then, the entity relationship between the multiple entities is determined for the processed data information, such as the relationship between charity organizations and charity projects, the relationship between social hot spots and charity projects, etc. Finally, the target knowledge graph is constructed through multiple entities and entity relationships, for example, Figure 3 The target knowledge graph corresponding to the donation information shown.

[0055] By building a knowledge graph, we can better analyze users' donation behavior and donation evaluation, better evaluate users' donation contributions, and facilitate more accurate scoring of users in the future.

[0056] Optionally, in the blockchain-based data processing method provided in the embodiment of the present application, the target object is scored based on the target knowledge graph through the evaluation node in the blockchain to obtain the target score value, which includes: analyzing the target knowledge graph to obtain the donation portrait of the target object; and scoring the target object based on the donation portrait to obtain the target score value.

[0057] In an optional embodiment, scoring a target subject based on a target knowledge graph via evaluation nodes in a blockchain includes the following steps: First, analyzing the target knowledge graph to obtain a donation profile of the target subject. For example, different entity types are identified from the knowledge graph, such as individual donors, corporate donors, and charitable organizations. Entities are then classified to understand user donation behavior, and relationships between entities are analyzed, such as those between donors and recipient organizations, and between donation projects. This relationship analysis can reveal donor preferences and donation patterns, as well as analyze entity attributes such as the donor's donation history, donation amount range, and donation frequency, ultimately yielding a user donation profile.

[0058] Target donors are scored using their donation profiles to obtain a target score. For example, key dimensions within the donation profile are identified, including donation amount, frequency, donor loyalty, and donor engagement. A scoring model is then constructed based on these key dimensions. This model can be linear or more complex, based on machine learning. Weights are then assigned to each scoring dimension, determined through expert scoring, historical data analysis, or donor surveys. Finally, the score for each donor is calculated using the following formula: Score = w1 × score for dimension 1 + w2 × score for dimension 2 + … + wn × score for dimension n.

[0059] Scoring users through donation profiles allows for the quantification of their donation contributions, which helps in matching users with better loan processing strategies based on their donation information.

[0060] Optionally, in the blockchain-based data processing method provided in the embodiment of the present application, the target knowledge graph is analyzed to obtain a donation portrait of the target object, including: obtaining a donation time feature value based on the time span information in the target knowledge graph; obtaining a donation frequency feature value based on the number of donations information in the target knowledge graph; obtaining a donation amount feature value based on the donation amount information in the target knowledge graph; obtaining a donation tendency feature value based on the donation project information and historical hot events in the target knowledge graph; and obtaining a donation portrait of the target object based on the donation time feature value, the donation frequency feature value, the donation amount feature value and the donation tendency feature value.

[0061] In an optional embodiment, the following steps can be used to obtain the user's donation portrait: obtain the donation time feature value based on the time span information in the target knowledge graph, for example, the length of time from the first donation to the most recent donation, and at the same time calculate the percentile value in the entire group, and use the percentile value as the above-mentioned donation time feature value.

[0062] The donation frequency feature value is obtained based on the number of donations in the target knowledge graph, for example, the number of times the donation was made within the donation time span, and the percentile value in the entire group is counted, and the percentile value is used as the above-mentioned donation frequency feature value.

[0063] The donation amount feature value is obtained based on the donation amount information in the target knowledge graph. For example, the donation amount and the corresponding donated materials are converted into amounts, the cumulative amount of participating donation funds is accumulated, and the percentile value in the entire group is calculated, and the percentile value is used as the above-mentioned donation amount feature value.

[0064] The donation tendency feature value is obtained based on the donation project information and historical hot events in the target knowledge graph. For example, the donation project information and historical hot events are clustered to obtain the donor's donation tendency, and then the donation tendency feature value is obtained.

[0065] Finally, based on the donation time characteristic value, donation frequency characteristic value, donation amount characteristic value and donation tendency characteristic value, the donation profile of the target object is obtained.

[0066] The donation time characteristic value, donation frequency characteristic value, donation amount characteristic value and donation tendency characteristic value can better evaluate the user's donation behavior information, which is convenient for subsequent user scoring.

[0067] Optionally, in the blockchain-based data processing method provided in the embodiment of the present application, obtaining the donation tendency feature value based on the donation project information and historical hot events in the target knowledge graph includes: classifying the donation tendency of the target object based on the donation project information and historical hot events through a decision tree to obtain a first donation tendency project; processing the donation project information and historical hot events through a support vector machine to obtain a second donation tendency project; and obtaining the donation tendency feature value based on the first donation tendency project and the second donation tendency project.

[0068] In an optional embodiment, the following steps are used to obtain a donation tendency characteristic value: using a decision tree to classify the target object's donation tendency based on donation project information and historical hot events to obtain a first donation tendency project, and using a vector machine to perform cluster analysis on the donation project information and historical hot events to obtain a second donation tendency project, and finally obtaining a donation tendency characteristic value based on the first donation tendency project and the second donation tendency project. For example, a target donation tendency project is obtained based on overlapping projects in the first donation tendency project and the second donation tendency project, and the target donation tendency project is vectorized to obtain the above-mentioned donation tendency characteristic value.

[0069] Decision trees and vector machines can more accurately analyze users' donation tendency items and improve the accuracy of determining donation tendency feature values.

[0070] Optionally, in the blockchain-based data processing method provided in the embodiment of the present application, after scoring the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain the target score value, the method also includes: determining the target digital collection based on the target score value; and performing consensus processing on the target digital collection in the blockchain, wherein the target digital collection is used by the target object to conduct business with a third party partner.

[0071] In an optional embodiment, after obtaining the target score, a corresponding target digital collection can be matched and a consensus process is performed on the blockchain. After consensus, the digital collection is issued to the donor and made available to the donor for inquiry via SMS, H5, etc. This target digital collection can then be used as proof of charitable donation in other subsequent services. By matching the target digital collection, a user's donation behavior over a specific time period can be clearly understood, which can encourage more people to participate in donations and increase the social impact of donations.

[0072] In an alternative embodiment, the Figure 4 The flowchart shown in the figure processes donation data, obtains various donation records, identifies donors based on these records, and optimizes and improves personal information such as user name, ID number, bank card number, mobile phone number, and third-party payment account. Donation records are analyzed and integrated, for example, to create a donation information map (including donation organization, donation project, donation finance, donation material, and donation time). Then, based on hot events, it generates public opinion hotspot information. Finally, based on the donation information map and public opinion hotspot information, it generates the user's target knowledge map.

[0073] In an alternative embodiment, the Figure 5 The flowchart shown implements the processing of donation data, specifically including: pre-processing such as standardization and normalization of user donation data, statistical analysis and record analysis of processed donation items, hot events, donation duration, frequency and total amount to obtain donor portraits, processing donor portraits according to the expert decision model to obtain scores, and issuing digital collections based on the scores.

[0074] In an optional embodiment, the block chain structure diagram is as follows Figure 6 As shown, the blockchain includes a donation registration node, an analysis node, an evaluation node, and a digital collection node. The donation registration node obtains the target object's historical donation information. The analysis node processes this historical donation information to obtain the target object's corresponding target knowledge graph. The evaluation node scores the target object based on the target knowledge graph and obtains a target score. The digital collection node determines matching digital collections based on the target score.

[0075] The blockchain-based data processing method provided in an embodiment of the present application obtains historical donation information of a target object through a donation registration node in the blockchain, wherein the historical donation information includes at least: attribute information of the target object, donation project information, donation time information, and donation amount information; processes the historical donation information through an analysis node in the blockchain to obtain a target knowledge graph corresponding to the target object; scores the target object based on the target knowledge graph through an evaluation node in the blockchain to obtain a target score value, and determines a processing strategy for a loan business to be processed by the target object based on the target score value, wherein, according to the processing strategy, a target knowledge graph corresponding to the target object is constructed through the analysis node in the blockchain, and the evaluation node scores the target object based on the target knowledge graph to determine the processing strategy for the loan business, thereby achieving the purpose of more accurately matching the processing strategy for the loan business. In addition, by matching the corresponding loan business strategy through donation information, the technical effect of stimulating the development of charitable business can also be achieved, thereby solving the technical problem in the related art of matching the corresponding business strategy for the user's pending loan business based on the user's historical transaction data, resulting in poor matching effect.

[0076] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0077] Example 2

[0078] The present application also provides a blockchain-based data processing device. It should be noted that the blockchain-based data processing device of the present application can be used to execute the blockchain-based data processing method provided in the present application. The following describes the blockchain-based data processing device provided in the present application.

[0079] According to an embodiment of the present application, a device for implementing the above-mentioned blockchain-based data processing method is also provided, such as Figure 7 As shown, the device includes: an acquisition unit 701, a processing unit 702 and a scoring unit 703.

[0080] An acquisition unit 701 is configured to acquire historical donation information of a target object through a donation registration node in a blockchain, wherein the historical donation information includes at least: attribute information of the target object, donation project information, donation time information, and donation amount information;

[0081] Processing unit 702, configured to process historical donation information through analysis nodes in the blockchain to obtain a target knowledge graph corresponding to the target object;

[0082] The scoring unit 703 is used to score the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain a target score value, and determine the processing strategy for the target object's loan business based on the target score value, wherein the loan business is processed for the target object according to the processing strategy.

[0083] The data processing device based on blockchain provided by the embodiment of the present application, through the acquisition unit 701, obtains the historical donation information of the target object through the donation registration node in the blockchain, wherein the historical donation information includes at least: the attribute information of the target object, the donation project information, the donation time information and the donation amount information; the processing unit 702 processes the historical donation information through the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object; the scoring unit 703 scores the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain a target score value, and determines the processing strategy of the target object's pending loan business based on the target score value, wherein the loan business is processed for the target object based on the processing strategy, solving the technical problem of matching the corresponding business strategy for the user's pending loan business based on the user's historical transaction data in the related art, resulting in poor matching effect. The target knowledge graph corresponding to the target object is constructed by the analysis node in the blockchain, and the evaluation node scores the target object based on the target knowledge graph to determine the loan business processing strategy, thereby achieving the purpose of more accurately matching the loan business processing strategy, and matching the corresponding loan business strategy through donation information can also achieve the technical effect of stimulating the development of charitable business.

[0084] Optionally, in the blockchain-based data processing device provided in an embodiment of the present application, the processing unit includes: an acquisition subunit, used to obtain historical hot events within the historical time period corresponding to the historical donation information; a processing subunit, used to pre-process the historical hot events and historical donation information to obtain processed data information; and a construction subunit, used to construct a target knowledge graph of the target object based on the processed data information.

[0085] Optionally, in the blockchain-based data processing device provided in an embodiment of the present application, the construction subunit includes: an identification module, used to perform entity recognition on the processed data information to obtain multiple entities; a first determination module, used to determine the entity relationship between multiple entities based on the processed data information; and a construction module, used to construct a target knowledge graph based on multiple entities and entity relationships.

[0086] Optionally, in the blockchain-based data processing device provided in an embodiment of the present application, the scoring unit includes: an analysis subunit, used to analyze the target knowledge graph to obtain a donation portrait of the target object; and a scoring subunit, used to score the target object based on the donation portrait to obtain a target scoring value.

[0087] Optionally, in the blockchain-based data processing device provided in the embodiment of the present application, the analysis subunit includes: a first processing module, used to obtain a donation time feature value based on the time span information in the target knowledge graph; a second processing module, used to obtain a donation frequency feature value based on the number of donations information in the target knowledge graph; a third processing module, used to obtain a donation amount feature value based on the donation amount information in the target knowledge graph; a fourth processing module, used to obtain a donation tendency feature value based on the donation project information and historical hot events in the target knowledge graph; a second determination module, used to obtain a donation portrait of the target object based on the donation time feature value, the donation frequency feature value, the donation amount feature value and the donation tendency feature value.

[0088] Optionally, in the blockchain-based data processing device provided in the embodiment of the present application, the fourth processing module includes: a classification submodule, which is used to classify the donation tendency of the target object based on the donation project information and historical hot events through a decision tree to obtain a first donation tendency project; a processing submodule, which is used to process the donation project information and historical hot events through a support vector machine to obtain a second donation tendency project; and a determination submodule, which is used to obtain a donation tendency feature value based on the first donation tendency project and the second donation tendency project.

[0089] Optionally, in the blockchain-based data processing device provided in the embodiment of the present application, the device also includes: a determination unit, which is used to score the target object based on the target knowledge graph through the evaluation node in the blockchain, and after obtaining the target score value, determine the target digital collection based on the target score value; a consensus unit, which is used to perform consensus processing on the target digital collection in the blockchain, wherein the target digital collection is used for the target object to conduct business with a third party partner.

[0090] It should be noted that the acquisition unit 701, processing unit 702, and scoring unit 703 correspond to steps S201 to S203 in the first embodiment. The examples and application scenarios implemented by the three units and the corresponding steps are the same, but are not limited to the contents disclosed in the first embodiment. It should be noted that the modules or units can be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The modules can also be part of a device and can be run in the computer terminal 10 provided in the first embodiment.

[0091] Example 3

[0092] An embodiment of the present application may provide an electronic device, Figure 8 This is a structural block diagram of an electronic device according to an embodiment of the present application. Figure 8 As shown, the electronic device may include: one or more ( Figure 8 Only one is shown) processor 802, memory 804, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0093] Among them, the memory can be used to store software programs and modules, such as program instructions / modules corresponding to the methods and devices in the embodiments of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implementing the above-mentioned method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0094] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtaining the historical donation information of the target object through the donation registration node in the blockchain, wherein the historical donation information includes at least: attribute information of the target object, donation project information, donation time information and donation amount information; processing the historical donation information through the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object; scoring the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain the target scoring value, and determining the processing strategy of the loan business to be processed by the target object based on the target scoring value, wherein the loan business is processed for the target object according to the processing strategy.

[0095] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: processing the historical donation information through the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object, including: obtaining historical hot events in the historical time period corresponding to the historical donation information; pre-processing the historical hot events and historical donation information to obtain processed data information; and constructing the target knowledge graph of the target object based on the processed data information.

[0096] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: constructing a target knowledge graph of the target object based on the processed data information, including: performing entity recognition on the processed data information to obtain multiple entities; determining the entity relationship between multiple entities based on the processed data information; and constructing a target knowledge graph based on multiple entities and entity relationships.

[0097] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: scoring the target object based on the target knowledge graph through the evaluation node in the blockchain, and obtaining the target score value includes: analyzing the target knowledge graph to obtain the donation portrait of the target object; scoring the target object based on the donation portrait to obtain the target score value.

[0098] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: analyze the target knowledge graph to obtain the donation portrait of the target object, including: obtaining the donation time feature value based on the time span information in the target knowledge graph; obtaining the donation frequency feature value based on the donation number information in the target knowledge graph; obtaining the donation amount feature value based on the donation amount information in the target knowledge graph; obtaining the donation tendency feature value based on the donation project information and historical hot events in the target knowledge graph; obtaining the donation portrait of the target object based on the donation time feature value, donation frequency feature value, donation amount feature value and donation tendency feature value.

[0099] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtaining the donation tendency feature value based on the donation project information and historical hot events in the target knowledge graph, including: classifying the donation tendency of the target object based on the donation project information and historical hot events through a decision tree to obtain a first donation tendency project; processing the donation project information and historical hot events through a support vector machine to obtain a second donation tendency project; obtaining the donation tendency feature value based on the first donation tendency project and the second donation tendency project.

[0100] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: after scoring the target object based on the target knowledge graph through the evaluation node in the blockchain and obtaining the target scoring value, the method also includes: determining the target digital collection based on the target scoring value; and performing consensus processing on the target digital collection in the blockchain, wherein the target digital collection is used by the target object to conduct business with a third party partner.

[0101] It can be understood by those skilled in the art that Figure 8The structure shown is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (MID), a PAD, or other terminal devices. Figure 8 It does not limit the structure of the above electronic device. For example, the electronic device may also include Figure 8 More or fewer components (such as network interfaces, display devices, etc.) shown in, or with Figure 8 Different configurations shown.

[0102] A person skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0103] Example 4

[0104] The embodiments of the present application also provide a computer-readable storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the blockchain-based data processing method provided in the first embodiment.

[0105] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0106] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the steps of the blockchain-based data processing method.

[0107] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0108] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0110] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0111] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0113] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A data processing method based on blockchain, characterized in that: include: Obtaining historical donation information of the target object through the donation registration node in the blockchain, wherein the historical donation information at least includes: attribute information of the target object, donation project information, donation time information and donation amount information; Processing the historical donation information through the analysis node in the blockchain to obtain a target knowledge graph corresponding to the target object; The target object is scored based on the target knowledge graph by the evaluation node in the blockchain to obtain a target score value, and based on the target score value, a processing strategy for the loan business to be processed by the target object is determined, wherein the loan business is processed for the target object according to the processing strategy.

2. The method according to claim 1, characterized in that The historical donation information is processed by the analysis node in the blockchain to obtain the target knowledge graph corresponding to the target object, including: Acquire historical hot events within the historical time period corresponding to the historical donation information; Preprocessing the historical hot events and the historical donation information to obtain processed data information; Construct a target knowledge graph of the target object based on the processed data information.

3. The method according to claim 2, characterized in that Constructing the target knowledge graph of the target object based on the processed data information includes: Performing entity recognition on the processed data information to obtain multiple entities; Determining entity relationships among the plurality of entities based on the processed data information; The target knowledge graph is constructed based on the multiple entities and the entity relationships.

4. The method according to claim 1, characterized in that: Scoring the target object based on the target knowledge graph through the evaluation node in the blockchain, and obtaining the target scoring value includes: Analyze the target knowledge graph to obtain a donation profile of the target object; The target object is scored according to the donation portrait to obtain the target score value.

5. The method according to claim 4, characterized in that The target knowledge graph is analyzed to obtain a donation profile of the target object, including: Obtaining a donation time feature value according to the time span information in the target knowledge graph; Obtaining a donation frequency feature value according to the donation frequency information in the target knowledge graph; Obtaining a donation amount feature value according to the donation amount information in the target knowledge graph; Obtaining donation tendency feature values ​​according to donation project information and historical hot events in the target knowledge graph; A donation portrait of the target object is obtained according to the donation time characteristic value, the donation frequency characteristic value, the donation amount characteristic value and the donation tendency characteristic value.

6. The method according to claim 5, characterized in that According to the donation project information and historical hot events in the target knowledge graph, the donation tendency feature values ​​are obtained, including: Classifying the donation tendency of the target object based on the donation project information and the historical hot events through a decision tree to obtain a first donation tendency project; Processing the donation project information and the historical hot events through a support vector machine to obtain a second donation tendency project; The donation tendency characteristic value is obtained based on the first donation tendency item and the second donation tendency item.

7. The method according to claim 1, characterized in that After scoring the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain a target scoring value, the method further includes: Determining the target digital collection according to the target scoring value; A consensus process is performed on the target digital collection in the blockchain, wherein the target digital collection is used by the target object to conduct business with a third party partner.

8. A data processing device based on blockchain, characterized in that: include: An acquisition unit is used to acquire historical donation information of a target object through a donation registration node in a blockchain, wherein the historical donation information at least includes: attribute information of the target object, donation project information, donation time information, and donation amount information; A processing unit, configured to process the historical donation information through an analysis node in the blockchain to obtain a target knowledge graph corresponding to the target object; A scoring unit is used to score the target object based on the target knowledge graph through the evaluation node in the blockchain to obtain a target scoring value, and determine a handling strategy for the loan business to be handled by the target object based on the target scoring value, wherein the loan business is handled for the target object according to the handling strategy.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the blockchain-based data processing method described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program, when running, executes the blockchain-based data processing method described in any one of claims 1 to 7.

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