CN112508621A - Transaction analysis method and device - Google Patents
Transaction analysis method and device Download PDFInfo
- Publication number
- CN112508621A CN112508621A CN202011477460.5A CN202011477460A CN112508621A CN 112508621 A CN112508621 A CN 112508621A CN 202011477460 A CN202011477460 A CN 202011477460A CN 112508621 A CN112508621 A CN 112508621A
- Authority
- CN
- China
- Prior art keywords
- information
- transaction
- block chain
- cloud platform
- customer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 25
- 230000008569 process Effects 0.000 claims abstract description 9
- 230000006399 behavior Effects 0.000 claims description 53
- 238000012545 processing Methods 0.000 claims description 19
- 238000012795 verification Methods 0.000 claims description 19
- 238000007619 statistical method Methods 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 13
- 238000004590 computer program Methods 0.000 description 7
- 238000000605 extraction Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000013506 data mapping Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000007781 pre-processing Methods 0.000 description 3
- 238000013480 data collection Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0203—Market surveys; Market polls
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Physics & Mathematics (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Economics (AREA)
- Probability & Statistics with Applications (AREA)
- Game Theory and Decision Science (AREA)
- Technology Law (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Computing Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a transaction analysis method and a device, comprising the following steps: the method comprises the steps of obtaining transaction information and customer information from a block chain cloud platform, wherein the customer information is obtained by the block chain cloud platform through a financial transaction platform, determining an incidence relation between the transaction information and the customer information, uploading the transaction information and the customer information with the incidence relation to a block chain through the block chain cloud platform, obtaining consumption behavior data of a customer to be analyzed from the block chain cloud platform, and storing the consumption behavior data into a database, wherein the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information with the incidence relation, so that various transactions of the customer are extracted from the block chain, and then statistical analysis is carried out, and therefore analysis is carried out on the transactions which have been submitted by the customer in the block chain.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a transaction analysis method and a transaction analysis device.
Background
The blockchain technology is a new technology which is started in recent years, does not need a third-party organization to participate, and has the characteristics of decentralization, openness, anonymity, non-tampering and the like. In a narrow sense, the blockchain is a distributed account book which is a chain data structure formed by combining data blocks in a sequential connection mode according to a time sequence and is guaranteed in a cryptographic mode and cannot be tampered and forged. Broadly speaking, the blockchain technology is a brand new distributed infrastructure and computing paradigm that uses blockchain data structures to verify and store data, uses distributed node consensus algorithms to generate and update data, uses cryptography to secure data transmission and access, and uses intelligent contracts composed of automated script codes to program and manipulate data.
The transaction in the blockchain is public, but the information of the consuming client and the corresponding multiple consumption details cannot be collected in the blockchain, and then statistical analysis is performed, and in the prior art, the statistical analysis of the data is directed to the big data and is not a transaction that has already been committed, so a transaction analysis method for performing statistical analysis on the information of the consuming client and the corresponding multiple consumption details in the blockchain is needed.
Disclosure of Invention
The embodiment of the invention provides a transaction analysis method and device, which are used for realizing.
In a first aspect, an embodiment of the present invention provides a transaction analysis method, including:
acquiring transaction information and customer information from a blockchain cloud platform; the customer information is acquired by the block chain cloud platform through a financial transaction platform;
determining the incidence relation between the transaction information and the customer information, and uploading the transaction information and the customer information with the incidence relation to a block chain through the block chain cloud platform;
acquiring consumption behavior data of a customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database; the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information which have the incidence relation.
In the technical scheme, the consumption behavior data of the customer to be analyzed is obtained from the block chain cloud platform and stored in the database, wherein the consumption behavior data of the customer to be analyzed is obtained after the block chain cloud platform processes the transaction information and the customer information with the association relationship, so that various transactions of the customer are extracted from the block chain, then statistical analysis is carried out, and the analysis of the transactions of the customer in the block chain is realized, namely the transaction which is already committed is analyzed, but not big data.
Optionally, before obtaining the transaction information and the customer information from the blockchain cloud platform, the method further includes:
customer information acquired by the block chain cloud platform from the financial transaction platform;
and the block chain cloud platform encrypts the customer information and uploads the customer information to the block chain.
Optionally, determining the association relationship between the transaction information and the customer information includes:
determining customer information and transaction information with an association relation according to the unique identification of each customer;
carrying out classified statistics on the customer information and the transaction information with the incidence relation according to keywords;
and sending the classified and counted customer information and transaction information to the block chain platform.
In the technical scheme, the customer information and the transaction information with the association relation are classified, so that the customer information and the transaction information with the association relation of the same category are stored in one block, and the data searching efficiency is improved.
Optionally, the consumption behavior data is obtained by processing, by the blockchain cloud platform, the transaction information and the customer information having the association relationship, and includes:
aiming at any client, the block chain cloud platform maps the transaction information of the client to obtain corresponding transaction characteristics, and consumption behavior data corresponding to the client and the trust degree of the client are determined according to the transaction characteristics;
and uploading the consumption behavior data of the client and the trust degree of the client to a block chain by the block chain cloud platform, and determining block information corresponding to the client.
Optionally, acquiring consumption behavior data of a customer to be analyzed from the blockchain cloud platform and storing the consumption behavior data in a database, including:
acquiring consumption behavior data of each client and the trust degree of each client from the block chain cloud platform according to the block information corresponding to each client;
and storing the client information, the block information and the consumption behavior data of each client with the trust degree greater than the trust threshold value into a non-relational database according to a preset analysis requirement.
In the technical scheme, the non-relational database can clearly and clearly store the relevant data of the client, and is applied to improving the data analysis efficiency.
Optionally, the method further includes:
acquiring query information input by a user;
and determining a feedback query result aiming at the query information according to the query information input by the user and the database.
Optionally, before the user inputs the query information, the method further includes:
displaying a plurality of preset problems and acquiring verification information input by a user;
and after the verification information passes the verification, granting the user data access right.
In the technical scheme, the data access of real workers can be ensured through various verification modes, and the data security is improved.
In a second aspect, an embodiment of the present invention provides a transaction analysis apparatus, including:
the acquisition unit is used for acquiring transaction information and customer information from the blockchain cloud platform; the customer information is acquired by the block chain cloud platform through a financial transaction platform;
the processing unit is used for determining the incidence relation between the transaction information and the customer information and uploading the transaction information and the customer information with the incidence relation to the block chain through the block chain cloud platform;
acquiring consumption behavior data of a customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database; the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information which have the incidence relation.
Optionally, the processing unit is specifically configured to:
determining customer information and transaction information with an association relation according to the unique identification of each customer;
carrying out classified statistics on the customer information and the transaction information with the incidence relation according to keywords;
and sending the classified and counted customer information and transaction information to the block chain platform.
Optionally, the processing unit is specifically configured to:
acquiring consumption behavior data of each client and the trust degree of each client from the block chain cloud platform according to the block information corresponding to each client;
and storing the client information, the block information and the consumption behavior data of each client with the trust degree greater than the trust threshold value into a non-relational database according to a preset analysis requirement.
Optionally, the processing unit is further configured to:
the control acquisition unit acquires query information input by a user;
and determining a feedback query result aiming at the query information according to the query information input by the user and the database.
Optionally, the processing unit is further configured to:
before a user inputs query information, displaying a plurality of preset problems and acquiring verification information input by the user;
and after the verification information passes the verification, granting the user data access right.
In a third aspect, an embodiment of the present invention further provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the transaction analysis method according to the obtained program.
In a fourth aspect, the present invention also provides a computer-readable storage medium, where computer-executable instructions are stored, and the computer-executable instructions are configured to enable a computer to execute the above transaction analysis method.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a system architecture diagram according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a transaction analysis method according to an embodiment of the present invention;
fig. 3 is a schematic system structure diagram of a block chain cloud platform according to an embodiment of the present invention;
fig. 4 is a schematic flow chart of data query according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a transaction analysis device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 exemplarily shows a system architecture to which an embodiment of the present invention is applicable, and the system architecture includes an information analysis and extraction unit 100, an input unit 110, an icon generation unit 120, and a display unit 130.
The information analysis and extraction unit 100 is configured to connect to a block chain cloud platform, and acquire block information and consumption behavior data of each client.
The input unit 110 is configured to obtain query information input by a user, and send the query information to the information analysis and extraction unit 100, so that the information analysis and extraction unit 100 confirms a feedback query result according to the query information.
An icon generating unit 120, configured to generate display frames such as images, characters, and lists according to the feedback query result;
the display unit 130 displays a display screen such as an image, a character, and a list generated by the icon generation unit 120.
It should be noted that the structure shown in fig. 1 is only an example, and the embodiment of the present invention is not limited thereto.
Based on the above description, fig. 2 is a schematic flow chart illustrating a transaction analysis method according to an embodiment of the present invention, where the flow chart is executed by a transaction analysis device.
As shown in fig. 2, the process specifically includes:
In the embodiment of the invention, the customer information is acquired by the block chain cloud platform through the financial transaction platform, wherein the customer information comprises the name, sex, age, education way, contact way, whether a membership card is used or not, the type of the membership card, the use limit of the membership card, card opening time, consumption place, consumption membership card number, consumption type, consumption amount, consumption number, consumption way and other information of a customer, the financial transaction platform can comprise endorsement mechanisms such as a third-party online financial transaction server, a customer online financial transaction terminal, a third-party operation platform and the like, and the transaction information is transaction information corresponding to the customer information.
Before transaction information and customer information are obtained from the blockchain cloud platform, the blockchain cloud platform obtains the customer information from the financial transaction platform, and then the blockchain cloud platform encrypts the customer information and uploads the customer information to the blockchain.
Fig. 3 exemplarily shows a system structure diagram of a blockchain cloud platform, and as shown in fig. 3, the system structure of the blockchain cloud platform includes a data manipulation module 300, a data collection module 310, a data encryption module 320, an information storage module 330, a sending module 340, a data mapping module 350, and a confidence calculation module 360, where the data manipulation module 300 is connected to the data collection module 310, the data encryption module 320, the information storage module 330, the sending module 340, the data mapping module 350, and the confidence calculation module 360.
The data manipulation module 300 is used for controlling the data acquisition module 310 to acquire the customer information from the financial transaction platform, and then manipulating the data encryption module 320 to encrypt the customer information, and then store the encrypted customer information in the information storage module 330.
In the embodiment of the invention, the customer information and the transaction information with the association relation are determined according to the unique identification of each customer, then the customer information and the transaction information with the association relation are classified and counted according to the keywords, and then the classified and counted customer information and transaction information are sent to the block chain platform. The keywords can be sex, age group, income, transaction frequency, average transaction amount, month and annual transaction amount, and the unique identification of the customer can be the identity card number, mobile phone number and the like of the customer.
For example, the customer information may be divided into two categories according to gender, the customers may be divided into 3 categories according to age group, or the customer information may be divided into six categories by using a combination of gender and age group as a keyword, a specific classification manner is not limited herein, and then the classified customer information is counted to obtain a statistical number and corresponding transaction information is counted.
And step 230, acquiring consumption behavior data of the customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database.
In the embodiment of the invention, the consumption behavior data is obtained by processing the transaction information and the customer information with the association relationship by the blockchain cloud platform.
Further, for any client, the block chain cloud platform maps the transaction information of the client to obtain corresponding transaction characteristics, and then determines consumption behavior data corresponding to the client and the trust degree of the client according to the transaction characteristics, wherein the block chain cloud platform uploads the consumption behavior data of the client and the trust degree of the client to the block chain to determine the block information corresponding to the client.
For example, as shown in fig. 3, the data manipulation module 300 controls the sending module 340 to send the customer information obtained from the financial transaction platform, maps the transaction information of each customer through the manipulated data mapping module 350 to obtain corresponding transaction characteristics, determines consumption behavior data corresponding to each customer according to the transaction characteristics, and manipulates the trust degree calculation module 360 to calculate the trust degree of each customer according to the transaction information and the customer information after the association processing.
For example, the blockchain cloud platform determines a first transaction with a transaction amount of more than 1 ten thousand yuan of a client as a luxury goods transaction, determines that the client is used to buy luxury goods for consumption behavior data, determines a second transaction with a transaction article characteristic of red color of the client as a favorite color transaction, determines that the consumption behavior data of the client is favorite red, and is preset, and can be various, like a similar commodity which is favorite with higher purchase price, better purchase evaluation, higher purchase price ratio and the like, which is not limited herein.
The tile information corresponding to each client includes, but is not limited to, a type of the tile chain, a version of the tile chain, a tile height, a timestamp, a transaction hash, a transaction signature, and the like.
After the consumption behavior data of the clients to be analyzed are obtained, the consumption behavior data of the clients and the trust degree of the clients are obtained from the block chain cloud platform according to the block information corresponding to the clients, and the client information, the block information and the consumption behavior data of the clients with the trust degree larger than the trust threshold are stored in the non-relational database according to the preset analysis requirements.
In the embodiment of the invention, after the client information, the block information and the consumption behavior data of each client with the trust degree greater than the trust threshold value are stored in the non-relational database according to the preset analysis requirement, the query information input by the user is obtained, and then the feedback query result aiming at the query information is determined according to the query information input by the user and the non-relational database. For example, if the query information input by the user is a down jacket, the query result is determined according to the consumption behavior data of the user in the non-relational database and fed back according to the characteristics of the down jacket, such as color, price, size and the like.
Illustratively, before the user inputs the query information, a plurality of preset questions are displayed, the verification information input by the user is acquired, and after the verification information passes the verification, the user data access authority is granted.
In the embodiment of the invention, the number of the preset questions can be multiple, for example, the number of the preset questions is 3, including favorite people, favorite mountains or past defaults and the like, when the user answers wrongly, the user is not given data access authority, and only after the verification information passes the verification, the user is given data access authority, so that the impersonation login of non-working personnel is prevented, and the information safety is ensured.
Specifically, the user data access authority further includes a plurality of preset authorities, and the accessed data content is different according to different authorities, for example, a user with a high authority can query more client information, block information and consumption behavior data of the client, and a user with a low authority can only query name information of the client and cannot query privacy information such as a mobile phone number of the client.
To better explain the above technical solution, fig. 4 exemplarily shows a flow diagram of data query, and as shown in fig. 4, the specific flow includes:
And extracting the block information and consumption behavior data corresponding to each client and the trust degree of each client from the block chain and the cloud platform.
And step 420, preprocessing data.
Determining a non-relational database and a preprocessing method according to the block information and the consumption behavior data corresponding to each client, the trust degree of each client and a preset analysis requirement, deleting the block information and the consumption behavior data of the client with the trust degree smaller than a trust threshold value according to the preprocessing method, and finally storing the preprocessed client information, block information and consumption behavior data of each client into the non-relational database.
And acquiring authentication information input by a user.
Before the user inputs the query information, displaying the date with the preset problem of birthday, and when the authentication information of the user is matched with the preset birthday date, the verification is passed, and executing the step 450, otherwise, executing the step 460.
The query information input by the user is acquired as follows: transaction amount per hour for 12 days in 12 months in 2010.
The user is not given access to the data.
And inquiring the transaction in the database according to the inquiry information of the user (the transaction amount per hour in 12 days in 12 months in 2010), and analyzing to obtain a feedback result (a chart of the transaction amount per hour in 12 days in 12 months in 2010, wherein the chart comprises the transaction amount per hour).
Based on the same technical concept, fig. 5 exemplarily shows a transaction analysis apparatus provided by an embodiment of the present invention, which may perform a flow of a transaction analysis method.
As shown in fig. 5, the apparatus specifically includes:
an obtaining unit 510, configured to obtain transaction information and customer information from a blockchain cloud platform; the customer information is acquired by the block chain cloud platform through a financial transaction platform;
the processing unit 520 is configured to determine an association relationship between the transaction information and the customer information, and upload the transaction information and the customer information having the association relationship into the blockchain through the blockchain cloud platform;
acquiring consumption behavior data of a customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database; the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information which have the incidence relation.
Optionally, the processing unit 520 is specifically configured to:
determining customer information and transaction information with an association relation according to the unique identification of each customer;
carrying out classified statistics on the customer information and the transaction information with the incidence relation according to keywords;
and sending the classified and counted customer information and transaction information to the block chain platform.
Optionally, the processing unit 520 is specifically configured to:
acquiring consumption behavior data of each client and the trust degree of each client from the block chain cloud platform according to the block information corresponding to each client;
and storing the client information, the block information and the consumption behavior data of each client with the trust degree greater than the trust threshold value into a non-relational database according to a preset analysis requirement.
Optionally, the processing unit 520 is further configured to:
the control acquiring unit 510 acquires query information input by a user;
and determining a feedback query result aiming at the query information according to the query information input by the user and the database.
Optionally, the processing unit 520 is further configured to:
before a user inputs query information, displaying a plurality of preset problems and acquiring verification information input by the user;
and after the verification information passes the verification, granting the user data access right.
Based on the same technical concept, an embodiment of the present invention further provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the transaction analysis method according to the obtained program.
Based on the same technical concept, the embodiment of the invention also provides a computer-readable storage medium, which stores computer-executable instructions for causing a computer to execute the transaction analysis method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A transaction analysis method, comprising:
acquiring transaction information and customer information from a blockchain cloud platform; the customer information is acquired by the block chain cloud platform through a financial transaction platform;
determining the incidence relation between the transaction information and the customer information, and uploading the transaction information and the customer information with the incidence relation to a block chain through the block chain cloud platform;
acquiring consumption behavior data of a customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database; the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information which have the incidence relation.
2. The method of claim 1, prior to obtaining transaction information and customer information from the blockchain cloud platform, further comprising:
customer information acquired by the block chain cloud platform from the financial transaction platform;
and the block chain cloud platform encrypts the customer information and uploads the customer information to the block chain.
3. The method of claim 1, wherein determining the association between the transaction information and the customer information comprises:
determining customer information and transaction information with an association relation according to the unique identification of each customer;
carrying out classified statistics on the customer information and the transaction information with the incidence relation according to keywords;
and sending the classified and counted customer information and transaction information to the block chain platform.
4. The method of claim 1, wherein the consumption behavior data is obtained by the blockchain cloud platform after processing the transaction information and the customer information with the association relationship, and comprises:
aiming at any client, the block chain cloud platform maps the transaction information of the client to obtain corresponding transaction characteristics, and consumption behavior data corresponding to the client and the trust degree of the client are determined according to the transaction characteristics;
and uploading the consumption behavior data of the client and the trust degree of the client to a block chain by the block chain cloud platform, and determining block information corresponding to the client.
5. The method of claim 4, wherein the step of obtaining and storing the consumption behavior data of the customer to be analyzed in the database through the blockchain cloud platform comprises:
acquiring consumption behavior data of each client and the trust degree of each client from the block chain cloud platform according to the block information corresponding to each client;
and storing the client information, the block information and the consumption behavior data of each client with the trust degree greater than the trust threshold value into a non-relational database according to a preset analysis requirement.
6. The method of any of claims 1 to 5, further comprising:
acquiring query information input by a user;
and determining a feedback query result aiming at the query information according to the query information input by the user and the database.
7. The method of claim 6, prior to the user entering query information, further comprising:
displaying a plurality of preset problems and acquiring verification information input by a user;
and after the verification information passes the verification, granting the user data access right.
8. A transaction analysis device, comprising:
the acquisition unit is used for acquiring transaction information and customer information from the blockchain cloud platform; the customer information is acquired by the block chain cloud platform through a financial transaction platform;
the processing unit is used for determining the incidence relation between the transaction information and the customer information and uploading the transaction information and the customer information with the incidence relation to the block chain through the block chain cloud platform;
acquiring consumption behavior data of a customer to be analyzed from the block chain cloud platform and storing the consumption behavior data into a database; the consumption behavior data is obtained after the block chain cloud platform processes the transaction information and the customer information which have the incidence relation.
9. A computing device, comprising:
a memory for storing program instructions;
a processor for calling program instructions stored in said memory to perform the method of any of claims 1 to 7 in accordance with the obtained program.
10. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011477460.5A CN112508621A (en) | 2020-12-15 | 2020-12-15 | Transaction analysis method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011477460.5A CN112508621A (en) | 2020-12-15 | 2020-12-15 | Transaction analysis method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112508621A true CN112508621A (en) | 2021-03-16 |
Family
ID=74973604
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011477460.5A Pending CN112508621A (en) | 2020-12-15 | 2020-12-15 | Transaction analysis method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112508621A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113436017A (en) * | 2021-07-07 | 2021-09-24 | 支付宝(杭州)信息技术有限公司 | Transaction processing method, device and equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109145201A (en) * | 2018-07-26 | 2019-01-04 | 百度在线网络技术（北京）有限公司 | A kind of approaches to IM based on block chain, device, equipment and storage medium |
| CN111091409A (en) * | 2019-10-31 | 2020-05-01 | 支付宝(杭州)信息技术有限公司 | Client tag determination method and device and server |
| CN111177202A (en) * | 2019-12-13 | 2020-05-19 | 浙商银行股份有限公司 | Supply chain financial system data query optimization method and platform based on block chain |
| CN111367965A (en) * | 2020-03-04 | 2020-07-03 | 腾讯云计算（北京）有限责任公司 | Target object determination method and device, electronic equipment and storage medium |
| WO2020233626A1 (en) * | 2019-05-20 | 2020-11-26 | 创新先进技术有限公司 | Receipt storage method and node in combination with conditional limitation of transaction and user types |
-
2020
- 2020-12-15 CN CN202011477460.5A patent/CN112508621A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109145201A (en) * | 2018-07-26 | 2019-01-04 | 百度在线网络技术（北京）有限公司 | A kind of approaches to IM based on block chain, device, equipment and storage medium |
| WO2020233626A1 (en) * | 2019-05-20 | 2020-11-26 | 创新先进技术有限公司 | Receipt storage method and node in combination with conditional limitation of transaction and user types |
| CN111091409A (en) * | 2019-10-31 | 2020-05-01 | 支付宝(杭州)信息技术有限公司 | Client tag determination method and device and server |
| CN111177202A (en) * | 2019-12-13 | 2020-05-19 | 浙商银行股份有限公司 | Supply chain financial system data query optimization method and platform based on block chain |
| CN111367965A (en) * | 2020-03-04 | 2020-07-03 | 腾讯云计算（北京）有限责任公司 | Target object determination method and device, electronic equipment and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113436017A (en) * | 2021-07-07 | 2021-09-24 | 支付宝(杭州)信息技术有限公司 | Transaction processing method, device and equipment |
| CN113436017B (en) * | 2021-07-07 | 2022-06-21 | 支付宝(杭州)信息技术有限公司 | Transaction processing method, device and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11496452B2 (en) | Non-repeatable challenge-response authentication | |
| US20190236607A1 (en) | Transaction Aggregation and Multiattribute Scoring System | |
| CN112651841A (en) | Online business handling method and device, server and computer readable storage medium | |
| CN113726784A (en) | Network data security monitoring method, device, equipment and storage medium | |
| KR102375962B1 (en) | User-centered learning space matching integrated management system | |
| CN115080858A (en) | Data recommendation method and device under multi-party collaboration scene | |
| CN111353891A (en) | Auxiliary method and device for identifying suspicious groups in fund transaction data | |
| CN116738493B (en) | Data encryption storage method and device based on classification category | |
| CN112508621A (en) | Transaction analysis method and device | |
| CN113486316A (en) | User identity authentication method and device, electronic equipment and readable storage medium | |
| CN112507141A (en) | Investigation task generation method and device, computer equipment and storage medium | |
| CN116051269A (en) | Mortgage financing service data processing method and device based on blockchain and zero knowledge proof | |
| CN115063234A (en) | Image quality inspection method, server and system for credit card application | |
| CN115147197A (en) | Intelligent bid inviting management system | |
| CN115204993A (en) | Public resource electronic transaction management method and system based on electronic visa | |
| CN115099967A (en) | Supply chain-based enterprise owner social recommendation method and device and storage medium | |
| CN113657808A (en) | Personnel evaluation method, device, equipment and storage medium | |
| KR102068403B1 (en) | Method and system for enclosed type marketing based on qualification certification | |
| CN113779635B (en) | Medical data verification method, device, equipment and storage medium | |
| CN114553684B (en) | Method, device, computer equipment and storage medium for network point operation and maintenance | |
| Vijayalakshmi et al. | Face Detection for Secure Online Payment with Proxy Detection | |
| CN114004639B (en) | Method, device, computer equipment and storage medium for recommending preferential information | |
| CN115374422B (en) | Anti-disclosure electronic signature verification method based on block chain | |
| CN111984840B (en) | Online asset security display locking method and device | |
| CN114549187B (en) | Method and system for controlling marketing two-dimensional code use range by electronic bank |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |