CN112084348A - Method and device for determining relevance - Google Patents
Method and device for determining relevance Download PDFInfo
- Publication number
- CN112084348A CN112084348A CN202011034255.1A CN202011034255A CN112084348A CN 112084348 A CN112084348 A CN 112084348A CN 202011034255 A CN202011034255 A CN 202011034255A CN 112084348 A CN112084348 A CN 112084348A
- Authority
- CN
- China
- Prior art keywords
- fund flow
- financial products
- financial
- association
- flow direction
- 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
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- Finance (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The application provides a method and a device for determining a relevance, wherein the method comprises the following steps: constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow; and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph. The method and the device can determine the association degree of the financial products by utilizing the fund flow direction relation map and the map calculation technology based on the fund flow.
Description
Technical Field
The application relates to the field of artificial intelligence, in particular to a method and a device for determining a relevance degree.
Background
With the rapid development of economy in China, the deep integration of emerging technologies and financial industries represented by big data, cloud computing, artificial intelligence, block chains and the like is pushing the traditional financial industry to step into a fast lane of transition development, the economic interaction activities between people are increasing, and financial products developed by financial institutions are renewing continuously. Therefore, complex fund relationships are generated among different financial products, and the fund flow direction among the different financial products is difficult to grasp quickly, so that the management and planning of financial products by financial institutions are seriously hindered.
With the development of big data and artificial intelligence technology, the application of graph computing technology and knowledge graph effectively helps people to understand the big financial data. Nowadays, more and more financial institutions pay attention to the correlation between financial products, but the fund flow between financial products has no clear correlation diagram, so that the financial institutions cannot accurately calculate the correlation degree between the financial products, and further the financial institutions lack data support for management and prediction of the financial products.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a method and a device for determining the association degree, which can determine the association degree of a financial product by utilizing a fund flow direction relation map and a map calculation technology based on fund flow.
In order to solve the technical problem, the application provides the following technical scheme:
in a first aspect, the present application provides a method for determining a relevance, including:
constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow;
and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph.
Further, the constructing a fund flow direction relationship knowledge graph based on each financial product and the corresponding fund flow comprises:
generating fund flow weight amount among the financial products based on the financial products and corresponding fund flow to obtain weight relation among different financial products;
and importing the weight relationship among the different financial products into a graph database for relationship matching to obtain the fund flow direction relationship knowledge graph.
Further, the generating of the fund flow weight amount between the financial products based on the financial products and the corresponding fund flow to obtain the weight relationship between the different financial products includes:
performing entity extraction, attribute extraction and relationship extraction on each financial product according to each financial product and the corresponding capital flow;
and calculating the fund flow weight amount among the financial products according to the extraction result to obtain the weight relationship among different financial products.
Further, the calculating of the fund flow weight amount between the financial products according to the drawing result comprises:
respectively obtaining contribution proportions of the financial products corresponding to each outgoing chain of the fund flow direction relation knowledge graph according to the extraction result;
and generating the fund flow weight amount between the financial products corresponding to the outgoing chain according to the contribution proportion.
Further, the determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph includes:
assigning the initial association degree of each financial product;
and respectively determining the corresponding association degrees of the financial products according to the initial association degrees, the output degrees of the fund flow direction relation knowledge graph and the fund flow weight amount among the financial products.
In a second aspect, the present application provides an association degree determining apparatus, including:
the map construction unit is used for constructing a fund flow direction relation knowledge map based on each financial product and the corresponding fund flow;
and the association degree determining unit is used for determining the association degree corresponding to each financial product according to the fund flow direction relation knowledge graph.
Further, the map construction unit includes:
the weight generation module is used for generating fund flow weight amount among the financial products based on the financial products and the corresponding fund flow to obtain the weight relation among different financial products;
and the map generation module is used for importing the weight relationship among the different financial products into a map database for relationship matching to obtain the fund flow direction relationship knowledge map.
Further, the association degree determination unit includes:
the assignment module is used for assigning the initial association degree of each financial product;
and the association degree determining module is used for respectively determining the association degrees corresponding to the financial products according to the initial association degrees, the output degrees of the fund flow direction relation knowledge graph and the fund flow weight amount among the financial products.
In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the association determination method when executing the program.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the relevance determining method.
Aiming at the problems in the prior art, the application provides a method and a device for determining the degree of association, which can determine the degree of association of financial products by utilizing a fund flow direction relation map and a map calculation technology based on fund flow, clearly master the association among the financial products, promote differentiated services aiming at different financial products and improve the customer satisfaction.
Drawings
Fig. 1 is a general flowchart of a method for determining a degree of association in an embodiment of the present application;
FIG. 2 is a flow chart of construction of a fund flow direction relationship knowledge graph in an embodiment of the present application;
FIG. 3 is a schematic diagram of financial product relationships in an embodiment of the present application;
FIG. 4 is a flow chart illustrating obtaining a weight relationship between different financial products according to an embodiment of the present disclosure;
FIG. 5 is a flow chart illustrating the calculation of a value of a fund flow weight between each of the financial products in an embodiment of the present application;
FIG. 6 is a second schematic diagram of the relationship between financial products in the embodiment of the present application;
FIG. 7 is a flowchart illustrating an embodiment of the present disclosure for determining a degree of association corresponding to each financial product;
FIG. 8 is a schematic illustration of a fund flow relationship knowledge graph in an embodiment of the present application;
fig. 9 is a structural diagram of a relevance degree determining apparatus in the embodiment of the present application;
FIG. 10 is a block diagram of an atlas-building element in an embodiment of the application;
fig. 11 is a structural diagram of a relevance degree determining unit in the embodiment of the present application;
fig. 12 is a schematic structural diagram of an electronic device in an embodiment of the present application;
FIG. 13 shows PR values of twenty financial products in the example of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and 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 application.
Referring to fig. 1, in order to determine the association degree of a financial product by using a fund flow direction relationship map and a map calculation technology based on fund flow, the present application provides an association degree determination method, including:
s101: and constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow.
It will be appreciated that in an actual financial transaction scenario, financial institutions tend to launch a wide variety of financial products and involve a wide variety of concerns. These financial products may include: the term "cash deposit" is used herein to refer to any one of cash deposit, commission, fund, national debt, financial product, insurance, real precious metal, account precious metal bi-directional, deposit, reserve deposit, individual share option, account commodity, individual credit, credit card, periodic deposit, etc., but the present application is not limited thereto. In everyday business, these financial products generate a corresponding flow of funds, accompanied by the transaction actions of the customer. These fund flows record the amount of transactions between financial products. The fund flow direction relation knowledge graph can be constructed based on financial products and corresponding fund flows. In the fund flow relationship knowledge map, financial products are used as entities, balance and/or transaction amount of the financial products are used as attributes, and fund transfer between the financial products is used as a relationship.
S102: and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph.
It can be understood that the association degree of each financial product can be calculated by applying the PageRank algorithm in Spark GraphX according to the fund flow direction relation knowledge graph in the embodiment of the application. Specifically, the PageRank algorithm can calculate the PageRank value, referred to as PR value, corresponding to each financial product. The importance degree of each financial product can be determined by ranking the PR values, namely, the higher the PR value is, the higher the association degree of the financial product is, the higher the importance degree is, and the lower the importance degree is.
From the above description, the association degree determining method provided by the application can determine the association degree of the financial products by using the fund flow direction relation map and the graph calculation technology based on the fund flow, clearly master the association among the financial products, promote differentiated services for different financial products, and improve the customer satisfaction.
Referring to FIG. 2, a fund flow direction relationship knowledge graph is constructed based on each financial product and the corresponding fund flow, comprising:
s201: generating fund flow weight amount among the financial products based on the financial products and corresponding fund flow to obtain weight relation among different financial products;
s202: and importing the weight relationship among different financial products into a graph database for relationship matching to obtain a fund flow direction relationship knowledge graph.
It is understood that the present application includes five financial products, namely, current deposit, financing product, alternative payroll, other product (except alternative payroll) summary and other product (except financing product) summary in one embodiment. The fund flow between the five financial products can be seen in the arrow shown in fig. 3. Wherein, the transaction amount from the generation wage to the current deposit is a; the transaction amount flowing to the current deposit is summarized by other products (except for the generation wages) as b; the transaction amount from the current deposit to the financing product is c; the transaction amount summarized by the demand deposit flow to other products (financial products) is d; e is the initial value of the deposit in the period, f is the final value of the deposit in the period. Assuming that a part of the money amount is added to the demand deposit, the remaining money amount is changed from the initial value e to the final value f, and the changed money amount is f-e, then, in step S201, it is calculated how much money amount in f-e is from the payroll to be issued, and how much money amount is from other products (except for the payroll) to be summarized, that is, the money flow weight amount between each financial product is generated, and the weight relationship between different financial products is obtained.
If the weight relationship between different financial products exists, the financial products can be imported into a graph database for relationship matching, and finally, a fund flow direction relationship knowledge graph is formed. In the embodiment of the application, TigerGraph is selected as a graph database to be imported.
From the above description, the association degree determination method provided by the application can construct the fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow.
Referring to fig. 4, the step of generating the fund flow weight amount between financial products based on the financial products and the corresponding fund flow to obtain the weight relationship between different financial products includes:
s401: performing entity extraction, attribute extraction and relationship extraction on each financial product according to each financial product and the corresponding capital flow;
s402: and calculating the fund flow weight amount among the financial products according to the extraction result to obtain the weight relationship among different financial products.
It is understood that the present application includes five financial products, namely, current deposit, financing product, alternative payroll, other product (except alternative payroll) summary and other product (except financing product) summary in one embodiment. In the fund flow direction relation knowledge graph, each financial product is an entity, and when the fund flow direction relation knowledge graph is constructed, the financial products can be used as the entities of the fund flow direction relation knowledge graph, namely, entity extraction is carried out. In addition, the balance and/or transaction amount of each financial product belongs to the attribute of the financial product, and may be extracted as the attribute of each entity in the fund flow direction relation knowledge graph, that is, the attribute, corresponding to a, b, c, d, e, and f in S501. In addition, there are fund transfers between financial products, which may be used as a relationship in the fund flow relationship knowledge graph, i.e., a relationship extraction is performed, corresponding to the arrows or lines in fig. 3, 6 and 8.
After entity extraction, attribute extraction and relationship extraction are carried out on each financial product, an extraction result can be obtained. And calculating the fund flow weight amount among the financial products according to the extraction result to obtain the weight relationship among different financial products. The specific method is described in S501-S502.
From the above description, the association degree determining method provided by the present application can generate the fund flow weight amount between financial products based on the financial products and the corresponding fund flow, so as to obtain the weight relationship between different financial products.
Referring to fig. 5, calculating the money movement weight amount between the financial products according to the drawing result includes:
s501: respectively obtaining contribution proportions of the financial products corresponding to each outgoing chain of the fund flow direction relation knowledge graph according to the extraction result;
s502: and generating the fund flow weight amount between the financial products corresponding to the outgoing chain according to the contribution proportion.
It will be appreciated that, referring to FIG. 6, an embodiment of the present application includes five financial products, namely, current deposit, financing product, surcharges, other product (surcharges) summary and other product (surcharges) summary. The fund transaction relationship among the financial products is shown as arrows, wherein the transaction amount of the current deposit from the generation wage is a; the transaction amount flowing to the current deposit is summarized by other products (except for the generation wages) as b; the transaction amount from the current deposit to the financing product is c; the transaction amount summarized by the demand deposit flow to other products (financial products) is d; e is the initial value of the deposit in the period, f is the final value of the deposit in the period. Assuming that the demand deposit is increased by a part of the amount, the rest amount is changed from the initial value e to the final value f.
In a fund flow relationship knowledge graph, the flow of funds from one entity to another is referred to as an out-link. According to the method and the device, the contribution proportion of each financial product corresponding to each outbound can be calculated according to the amount of money which flows out of the outbound. For example, if a person deposits 100 ten thousand RMB into a financial product of the current deposit, wherein 40 ten thousand RMB are derived from a financial product of the accredited wage, and 60 ten thousand RMB are derived from a financial product of another product, the accredited wage contributes 40% to the 100 ten thousand RMB deposited into the current deposit, the other product contributes 60% to the 100 ten thousand RMB deposited into the current deposit, and the above-mentioned 40% and 60% are the contribution ratio.
Referring to fig. 6, the fund flow weight amount between the financial products corresponding to the outbound chain may be generated according to the contribution ratio, and the calculation method is as follows:
recording the fund flow weight amount of the surreptitious wage-financing product as A1, wherein A1 is (a/(a + b + e)) × (c/f) x f;
recording the surcharge wages to other products (except financing products) and setting the total fund flow weight amount to be A2, wherein A2 is (a/(a + b + e)) × (d/f) x f;
recording other products (except for the generation wages) and summarizing the fund flow weight sum of the financing product as B1, wherein B1 is (B/(a + B + e)) × (c/f) x f;
recording other products (except for the generation wages) and summarizing the other products (except for the financing products) to obtain a summarized fund flow weight amount of B2, wherein B2 is (B/(a + B + e)) × (c/f) x f;
the money flow weight amount of the credit to the financial product is C1, C1 ═ e/(a + b + e)) × (C/f) × f;
the total fund flow weight amount of the deposit in the keep-alive period to other products (except financing products) is C2, and C2 is (e/(a + b + e)) × (d/f) x f;
recording the payment of the surcharge to the current deposit fund flow weight amount D1, wherein D1 is a- (A1+ A2);
other products (except for generation wages) are recorded and gathered into the current deposit as D2, and D2 is B- (B1+ B2).
From the above description, the association degree determining method provided by the present application can generate the fund flow weight amount between the financial products corresponding to the outbound chain according to the contribution ratio.
Referring to fig. 7, determining the corresponding association degree of each financial product according to the fund flow direction relationship knowledge graph includes:
s701: assigning the initial association degree of each financial product;
s702: and respectively calculating the corresponding association degrees of the financial products according to the initial association degrees, the output degrees of the fund flow direction relation knowledge maps and the fund flow weight amount among the financial products.
It will be appreciated that, referring to FIG. 8, the fund flow relationship knowledge graph in the embodiments of the present application may form an interwoven mesh centered on demand deposits, with each line representing a fund relationship between two financial products, being a two-way fund relationship network.
The steps of S701-S702 are realized by a PageRank algorithm, and the PageRank is a method for calculating and sequencing the importance of the nodes in the graph. The importance of each node in the graph can be quantified by using a PageRank value (PR value for short). The basic idea is as follows: a certain node in the graph is associated with more other nodes, which shows that the more important the node is, the higher the corresponding PR value is; if a node with a high PR value is associated with other nodes, the PR value of the node associated with the node is increased accordingly.
Based on the two points, when the PageRank algorithm is used for determining the corresponding association degree of each financial product, each financial product needs to be given the initial association degree, and one financial product corresponds to one node. The initial relevance of each node is the same, and the PR value of each node can be updated through iterative recursive calculation until the PR values of all nodes tend to be stable.
The calculation formula of PR value of a node u in the fund flow direction relation knowledge graph is as follows:
wherein, BuIs a set of all nodes linked to node u, and node v belongs to set BuL (v) is the degree of departure of node v, Wv is the weight of node v, PR (v) and PR (u) arePR values for node v and node u. In this embodiment, the amount of the fund flow weight between financial products. The iteration results are shown in table 1:
TABLE 1
| PA(A) | P(B) | PR(C) | PR(D) | |
| Initial value | 0.25 | 0.25 | 0.25 | 0.25 |
| One iteration | 0.125 | 0.333 | 0.083 | 0.458 |
| Second iteration | 0.1665 | 0.4997 | 0.0417 | 0.2912 |
| …… | …… | …… | …… | …… |
| n iterations | 0.1999 | 0.3999 | 0.0666 | 0.3333 |
According to the above method, the PR values of twenty financial products in the embodiment of the present application can be obtained, see fig. 13.
From the above description, the association degree determining method provided by the application can determine the association degree corresponding to each financial product according to the fund flow direction relation knowledge graph.
Based on the same inventive concept, the embodiment of the present application further provides a relevance determining apparatus, which can be used to implement the methods described in the above embodiments, as described in the following embodiments. Because the principle of the relevance determining apparatus for solving the problem is similar to that of the relevance determining method, the relevance determining apparatus may be implemented by a software performance reference determining method, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. While the system described in the embodiments below is preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
Referring to fig. 9, in order to determine the association degree of a financial product by using a fund flow direction relationship map and a map calculation technique based on fund flow, the present application provides an association degree determining apparatus, including: an atlas constructing unit 901 and an association degree determining unit 902.
The map construction unit 901 is used for constructing a fund flow direction relation knowledge map based on each financial product and the corresponding fund flow;
and an association degree determining unit 902, configured to determine, according to the fund flow direction relationship knowledge graph, an association degree corresponding to each financial product.
Referring to fig. 10, the atlas constructing unit 901 includes: a weight generation module 1001 and a map generation module 1002.
A weight generation module 1001, configured to generate a fund flow weight amount between financial products based on each financial product and a corresponding fund flow, so as to obtain a weight relationship between different financial products;
the map generation module 1002 is configured to import the weight relationships between the different financial products into a map database for relationship matching, so as to obtain the fund flow direction relationship knowledge map.
Referring to fig. 11, the association degree determining unit 902 includes: an assignment module 1101 and an association determination module 1102.
An assignment module 1101 for assigning an initial association degree of each financial product;
and the association degree determining module 1102 is configured to determine association degrees corresponding to the financial products according to the initial association degrees, the degree of the fund flow direction relationship knowledge graph, and the fund flow weight amounts between the financial products.
In order to determine the association degree of a financial product based on fund flow by using a fund flow direction relationship map and a map calculation technology from a hardware level, the present application provides an embodiment of an electronic device having all or part of contents in an association degree determination method, where the electronic device specifically includes the following contents:
a Processor (Processor), a Memory (Memory), a communication Interface (Communications Interface) and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the relevancy determination device and relevant equipment such as a core service system, a user terminal, a relevant database and the like; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the logic controller may be implemented with reference to the embodiment of the association degree determining method and the embodiment of the association degree determining apparatus in the embodiments, and the contents thereof are incorporated herein, and repeated descriptions are omitted.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), an in-vehicle device, a smart wearable device, and the like. Wherein, intelligence wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical applications, part of the association degree determination method may be executed on the electronic device side as described in the above, or all operations may be completed in the client device. The selection may be specifically performed according to the processing capability of the client device, the limitation of the user usage scenario, and the like. This is not a limitation of the present application. The client device may further include a processor if all operations are performed in the client device.
The client device may have a communication module (i.e., a communication unit), and may be in communication connection with a remote server to implement data transmission with the server. The server may include a server on the side of the task scheduling center, and in other implementation scenarios, the server may also include a server on an intermediate platform, for example, a server on a third-party server platform that is communicatively linked to the task scheduling center server. The server may include a single computer device, or may include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.
Fig. 12 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 12, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 12 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, the association determination method function may be integrated into the central processor 9100. The central processor 9100 may be configured to control as follows:
s101: and constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow.
S102: and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph.
From the above description, the association degree determining method provided by the application can determine the association degree of the financial products by using the fund flow direction relation map and the graph calculation technology based on the fund flow, clearly master the association among the financial products, promote differentiated services for different financial products, and improve the customer satisfaction.
In another embodiment, the association degree determining apparatus may be configured separately from the central processor 9100, for example, the association degree determining apparatus may be configured as a chip connected to the central processor 9100, and the function of the association degree determining method may be implemented by the control of the central processor.
As shown in fig. 12, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 12; further, the electronic device 9600 may further include components not shown in fig. 12, which can be referred to in the related art.
As shown in fig. 12, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless lan module, may be disposed in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps of the association degree determining method in which an execution subject is a server or a client in the foregoing embodiments, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps of the association degree determining method in which the execution subject is a server or a client, for example, when the processor executes the computer program, the processor implements the following steps:
s101: and constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow.
S102: and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph.
From the above description, the association degree determining method provided by the application can determine the association degree of the financial products by using the fund flow direction relation map and the graph calculation technology based on the fund flow, clearly master the association among the financial products, promote differentiated services for different financial products, and improve the customer satisfaction.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. 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.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method for determining a degree of association, comprising:
constructing a fund flow direction relation knowledge graph based on each financial product and the corresponding fund flow;
and determining the corresponding association degree of each financial product according to the fund flow direction relation knowledge graph.
2. The method of determining relevancy of claim 1 wherein constructing a knowledge graph of fund flow relationships based on each financial product and corresponding fund flow comprises:
generating fund flow weight amount among the financial products based on the financial products and corresponding fund flow to obtain weight relation among different financial products;
and importing the weight relationship among the different financial products into a graph database for relationship matching to obtain the fund flow direction relationship knowledge graph.
3. The method of claim 2, wherein the generating a fund flow weight amount between financial products based on each financial product and a corresponding fund flow to obtain a weight relationship between different financial products comprises:
performing entity extraction, attribute extraction and relationship extraction on each financial product according to each financial product and the corresponding capital flow;
and calculating the fund flow weight amount among the financial products according to the extraction result to obtain the weight relationship among different financial products.
4. The association determination method according to claim 3, wherein the calculating of the money movement weight amount between the financial products based on the extraction result includes:
respectively obtaining contribution proportions of the financial products corresponding to each outgoing chain of the fund flow direction relation knowledge graph according to the extraction result;
and generating the fund flow weight amount between the financial products corresponding to the outgoing chain according to the contribution proportion.
5. The association determination method of claim 4, wherein determining the association corresponding to each financial product according to the fund flow direction relationship knowledge graph comprises:
assigning the initial association degree of each financial product;
and respectively determining the corresponding association degrees of the financial products according to the initial association degrees, the output degrees of the fund flow direction relation knowledge graph and the fund flow weight amount among the financial products.
6. An association degree determination apparatus, comprising:
the map construction unit is used for constructing a fund flow direction relation knowledge map based on each financial product and the corresponding fund flow;
and the association degree determining unit is used for determining the association degree corresponding to each financial product according to the fund flow direction relation knowledge graph.
7. The association degree determination apparatus according to claim 6, wherein the map construction unit includes:
the weight generation module is used for generating fund flow weight amount among the financial products based on the financial products and the corresponding fund flow to obtain the weight relation among different financial products;
and the map generation module is used for importing the weight relationship among the different financial products into a map database for relationship matching to obtain the fund flow direction relationship knowledge map.
8. The association degree determination device according to claim 7, wherein the association degree determination unit includes:
the assignment module is used for assigning the initial association degree of each financial product;
and the association degree determining module is used for respectively determining the association degrees corresponding to the financial products according to the initial association degrees, the output degrees of the fund flow direction relation knowledge graph and the fund flow weight amount among the financial products.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the association determination method according to any one of claims 1 to 5 are implemented when the processor executes the program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the relevance determination method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011034255.1A CN112084348A (en) | 2020-09-27 | 2020-09-27 | Method and device for determining relevance |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011034255.1A CN112084348A (en) | 2020-09-27 | 2020-09-27 | Method and device for determining relevance |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112084348A true CN112084348A (en) | 2020-12-15 |
Family
ID=73739978
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011034255.1A Pending CN112084348A (en) | 2020-09-27 | 2020-09-27 | Method and device for determining relevance |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112084348A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114064883A (en) * | 2022-01-17 | 2022-02-18 | 北京融华汇投资管理有限公司 | Medicine knowledge fast learning system and method based on precise algorithm and big data |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2779066A1 (en) * | 2013-03-14 | 2014-09-17 | Payfriendz Ltd. | Closed-loop mobile money transaction system |
| CN110399533A (en) * | 2019-07-29 | 2019-11-01 | 中国工商银行股份有限公司 | Funds flow querying method and device |
| CN111383005A (en) * | 2018-12-29 | 2020-07-07 | 北京知帆科技有限公司 | Digital currency flow direction tracking method and device |
| CN111708897A (en) * | 2020-06-11 | 2020-09-25 | 中国建设银行股份有限公司 | Target information determination method, device and equipment |
-
2020
- 2020-09-27 CN CN202011034255.1A patent/CN112084348A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2779066A1 (en) * | 2013-03-14 | 2014-09-17 | Payfriendz Ltd. | Closed-loop mobile money transaction system |
| CN111383005A (en) * | 2018-12-29 | 2020-07-07 | 北京知帆科技有限公司 | Digital currency flow direction tracking method and device |
| CN110399533A (en) * | 2019-07-29 | 2019-11-01 | 中国工商银行股份有限公司 | Funds flow querying method and device |
| CN111708897A (en) * | 2020-06-11 | 2020-09-25 | 中国建设银行股份有限公司 | Target information determination method, device and equipment |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114064883A (en) * | 2022-01-17 | 2022-02-18 | 北京融华汇投资管理有限公司 | Medicine knowledge fast learning system and method based on precise algorithm and big data |
| CN114064883B (en) * | 2022-01-17 | 2022-04-29 | 北京融华汇投资管理有限公司 | Medicine knowledge fast learning system and method based on precise algorithm and big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111861569B (en) | Product information recommendation method and device | |
| CN111951052B (en) | Method and device for acquiring potential clients based on knowledge graph | |
| CN110210899A (en) | Advertisement sending method, device and equipment based on advertisement similitude | |
| CN107146158A (en) | A kind of electronic data processing method and device | |
| CN110020662A (en) | The training method and device of user's disaggregated model | |
| CN110210898A (en) | Advertisement sending method, device and equipment based on user behavior | |
| CN110348947A (en) | Object recommendation method and device | |
| CN112084348A (en) | Method and device for determining relevance | |
| CN111553487B (en) | Business object identification method and device | |
| CN112561686A (en) | Method and system for evaluating credit line of supply chain enterprise | |
| CN112418929B (en) | Data sharing method and device | |
| CN116361542A (en) | Product recommendation method, device, computer equipment and storage medium | |
| US20230044461A1 (en) | Fully Collateralized Stablecoins that Pay a Fixed Rate of Interest | |
| CN108711043A (en) | A kind of fund keeps accounts method, apparatus, electronic equipment and computer-readable medium | |
| CN108256667A (en) | Asset data processing method, device, storage medium and computer equipment | |
| CN113343681A (en) | Enterprise financial service pushing method and device | |
| CN112417018A (en) | Data sharing method and device | |
| CN111369287A (en) | Information processing method, information processing device, computer storage medium and computer equipment | |
| CN110046911A (en) | Consume contract processing method and its system | |
| CN109584057A (en) | Transaction details data capture method, device and server | |
| Gumbo et al. | Perceived usefulness (PU) and perceived ease of use (PEOU) as key drivers of mobile banking adoption: a case of Zimbabwe | |
| CN113902554A (en) | User classification method, device and system based on machine learning | |
| CN112883259A (en) | Information pushing method and device | |
| CN115525843A (en) | Credit card bill staging service recommendation method and device | |
| CN113706288A (en) | Financing application admission determining method and device |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201215 |
|
| RJ01 | Rejection of invention patent application after publication |