CN111797406A

CN111797406A - Medical fund data analysis processing method and device and readable storage medium

Info

Publication number: CN111797406A
Application number: CN202010682585.5A
Authority: CN
Inventors: 梁成敏; 梁燕露; 杨乐忠
Original assignee: Zhiboyun Information Technology Guangzhou Co ltd
Current assignee: Hu Bingxiang
Priority date: 2020-07-15
Filing date: 2020-07-15
Publication date: 2020-10-20

Abstract

The invention discloses a medical fund data analysis processing method, a device and a readable storage medium, which relate to the technical field of data processing, and the medical fund data analysis processing method comprises the following steps: acquiring fund service operation data to be graded and analyzed from a fund data server; adding the fund service operation data which is subjected to rating analysis into a fund service knowledge graph; in response to a viewing request for uploading the fund service operation data which is subjected to the rating analysis to computer equipment, obtaining the fund service operation data which is subjected to the rating analysis from the first fund service knowledge graph, and determining target fund security information according to the obtained fund service operation data which is subjected to the rating analysis; generating a target fund operation safety evaluation report; and uploading the target fund operation safety assessment report to computer equipment, and analyzing the safety of the medical fund data to ensure the safety of the medical fund data.

Description

Medical fund data analysis processing method and device and readable storage medium

Technical Field

The invention relates to the technical field of data processing, in particular to a medical fund data analysis processing method and device and a readable storage medium.

Background

Currently, since various medical projects involve a large amount of research and development, and the prices of equipment, medicines and the like required for research and development are relatively expensive, in order to facilitate management and store project funds, funds are generally used as fund sources of various projects. However, the security of the related medical fund data is not guaranteed, and the situations of miscount, missed account, even false guarantee and the like may occur, and moreover, the medical fund with huge number also has a certain risk of being attacked by external illegal operations.

In view of the above, it is necessary for those skilled in the art to provide a solution capable of analyzing the security of medical fund data.

Disclosure of Invention

The invention provides a medical fund data analysis processing method, a medical fund data analysis processing device and a readable storage medium.

In a first aspect, an embodiment of the present invention provides a medical fund data analysis processing method, which is applied to a computer device, where the computer device is in communication connection with a fund data server, the fund data server stores a fund service knowledge graph, and the fund service knowledge graph includes a first fund service knowledge graph, and the first fund service knowledge graph is used for storing fund service operation data for which rating analysis is completed;

the method comprises the following steps:

obtaining fund service operation data to be rated and analyzed from the fund data server, and performing rating analysis processing on the fund service operation data to be rated and analyzed;

adding the fund service operation data subjected to rating analysis into the fund service knowledge graph, wherein the fund service operation data subjected to rating analysis is added into the first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data subjected to rating analysis, and the fund service operation data with a higher rating is more greatly compared with a preset safe matching value of the preset fund service reference operation parameters in the first fund service knowledge graph;

in response to a viewing request for uploading the fund service operation data completed by the rating analysis to the computer device, acquiring the fund service operation data completed by the rating analysis from the first fund service knowledge graph, and determining target fund security information according to the acquired fund service operation data completed by the rating analysis;

generating a target fund operation safety assessment report, wherein the target fund operation safety assessment report comprises the target fund safety information;

uploading the target fund operation security assessment report to the computer device.

Optionally, the fund service knowledge graph further includes a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a first early warning evaluation value, the second fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a second early warning evaluation value, the first early warning evaluation value is a preset safety matching value of preset fund service reference operation parameters obtained when the fund service operation data which is subjected to rating analysis is uploaded, the second early warning evaluation value is determined according to a data source of the fund service operation data which is subjected to rating analysis and received by the computer device, and the preset fund service reference operation parameters obtained when the fund service operation data which is subjected to rating analysis is uploaded to the computer device, fund service operation data stored by the first fund service knowledge graph is distributed in descending order from the first early warning evaluation value to low, and fund service operation data stored by the second fund service knowledge graph is distributed in descending order from the second early warning evaluation value to high;

the step of adding the fund service operation data completed by rating analysis to the fund service knowledge graph comprises the following steps:

adding the fund service operation data completed by the rating analysis to the second fund service knowledge graph;

the step of obtaining the fund service operation data completed by the rating analysis from the first fund service knowledge graph and determining target fund security information according to the obtained fund service operation data completed by the rating analysis comprises the following steps:

determining a preset rule for acquiring the fund service operation data which is subjected to rating analysis from the first fund service knowledge graph and the second fund service knowledge graph, wherein the preset rule comprises a first fund confidence corresponding to the first fund service knowledge graph and a second fund confidence corresponding to the second fund service knowledge graph;

acquiring a fund service operation data object set to be uploaded to the computer equipment;

determining a first proportion according to the fund service operation data object set and the first fund confidence coefficient, and determining a second proportion according to the fund service operation data object set and the second fund confidence coefficient;

acquiring fund service operation data with the first proportion from the first fund service knowledge graph according to the sequence of the first early warning evaluation value from high to low as a preset fund service reference operation parameter;

and acquiring the fund service operation data with the second proportion from the second fund service knowledge graph according to the sequence of the second early warning evaluation value from high to low as fund service operation data to be rated and analyzed, and determining the target fund safety information according to the preset fund service reference operation parameters and the fund service operation data to be rated and analyzed.

Optionally, the fund service operation data after rating analysis is further added to a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing the fund service operation data after rating analysis with a first early warning evaluation value, and the second fund service knowledge graph is used for representing the fund service operation data after rating analysis with a second early warning evaluation value;

the step of adding the fund service operation data completed by rating analysis to the fund service knowledge graph further comprises:

acquiring attribute information of fund service operation data subjected to rating analysis, and determining the first early warning evaluation value and the second early warning evaluation value of the fund service operation data subjected to rating analysis according to the attribute information;

and adding the fund service operation data subjected to rating analysis into the first fund service knowledge graph and the second fund service knowledge graph according to the first early warning evaluation value and the second early warning evaluation value of the fund service operation data subjected to rating analysis.

Optionally, the determining, according to the attribute information, the first warning evaluation value and the second warning evaluation value of the fund service operation data after the rating analysis is completed includes:

determining preset fund service reference operation parameters acquired when the fund service operation data subjected to rating analysis is uploaded to computer equipment, and determining a data source of the fund service operation data subjected to rating analysis received by the fund data server;

determining the first early warning evaluation value of the fund service operation data subjected to rating analysis in the first fund service knowledge graph according to the preset fund service reference operation parameter; and the number of the first and second groups,

and determining the second early warning evaluation value of the fund service operation data subjected to rating analysis in the second fund service knowledge graph according to the preset fund service reference operation parameter and the data source.

Optionally, the adding, according to the first warning evaluation value and the second warning evaluation value of the fund service operation data subjected to rating analysis, the fund service operation data subjected to rating analysis to the first fund service knowledge graph and the second fund service knowledge graph includes:

adding the fund service operation data subjected to rating analysis into the first fund service knowledge graph according to the first early warning evaluation value; and the number of the first and second groups,

and adding the fund service operation data subjected to rating analysis into the second fund service knowledge graph according to the second early warning evaluation value.

Optionally, the step of performing rating analysis processing on the fund business operation data to be rated and analyzed includes:

the fund service operation data appearing in the fund data server are counted to obtain a plurality of fund service operation data;

counting the occurrence times of the fund service operation data in the fund data server aiming at each fund service operation data in the plurality of fund service operation data;

if the occurrence frequency does not reach a first preset operation frequency threshold value, removing the fund service operation data from the plurality of fund service operation data;

respectively taking the plurality of fund service operation data as elements, and establishing logical association among fund service operation data which simultaneously appear in the same fund data server so as to establish a logical relationship table among the plurality of fund service operation data, wherein the logical relationship table is used for representing the association relationship among the plurality of fund service operation data;

selecting a preset fund service reference operation parameter from the plurality of fund service operation data, and determining a preset safety matching value corresponding to the preset fund service reference operation parameter according to the corresponding relation between the preset fund service reference operation parameter and each preset safety level operation;

for each fund service operation data to be rated and analyzed, respectively determining the correlation between the fund service operation data to be rated and analyzed and each fund service operation data adjacent to the fund service operation data to be rated and analyzed according to the weight of each logic association connected with the fund service operation data to be rated and analyzed;

determining a preset safety matching value of the fund service operation data to be graded and analyzed according to the correlation between the fund service operation data to be graded and each fund service operation data adjacent to the fund service operation data and the preset safety matching value of each fund service operation data adjacent to the fund service operation data, wherein, the preset security matching value corresponding to the preset fund service reference operation parameter and the preset security matching value corresponding to the fund service operation data to be graded and analyzed are respectively a security object data set, the number of security object data in the security object data set is the same as the number of preset security level operations, the safety object data in the safety object data set respectively represent the probability that the preset fund service reference operation parameters and the fund service operation data to be graded and analyzed respectively belong to each preset safety level operation;

determining the safety object data with the maximum value in the preset safety matching values corresponding to the fund service operation data to be graded and analyzed, and determining the preset safety level operation corresponding to the safety object data with the maximum value;

and determining the fund service operation data to be subjected to rating analysis as the fund service operation data to be subjected to rating analysis corresponding to the preset security level operation so as to finish rating analysis processing on the fund service operation data to be subjected to rating analysis.

Optionally, before the step of adding the rating analysis completed fund service operation data to the fund service knowledge-graph, the method further comprises:

acquiring a fund service operation data object set in the first fund service knowledge graph and a fund service operation data object set in the second fund service knowledge graph;

and when the fund service operation data object set in the first fund service knowledge graph is less than or equal to the fund service operation data object set in the second fund service knowledge graph, adding the fund service operation data subjected to rating analysis to the first fund service knowledge graph.

In a second aspect, an embodiment of the present invention provides a medical fund data analysis processing apparatus, which is applied to a computer device, the computer device is in communication connection with a fund data server, the fund data server stores a fund service knowledge graph, the fund service knowledge graph comprises a first fund service knowledge graph, and the first fund service knowledge graph is used for storing fund service operation data after rating analysis is completed;

the device comprises:

the acquisition module is used for acquiring fund service operation data to be subjected to rating analysis from the fund data server and performing rating analysis processing on the fund service operation data to be subjected to rating analysis;

an adding module, configured to add the fund service operation data subjected to rating analysis to the fund service knowledge graph, wherein the fund service operation data subjected to rating analysis is added to the first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data subjected to rating analysis, and in the first fund service knowledge graph, the fund service operation data with a larger preset security matching value of the preset fund service reference operation parameters is ranked higher;

a response module, configured to, in response to a viewing request for uploading the fund service operation data completed by the rating analysis to the computer device, obtain the fund service operation data completed by the rating analysis from the first fund service knowledge graph, and determine target fund security information according to the obtained fund service operation data completed by the rating analysis;

a generation module for generating a target fund operation security assessment report, wherein the target fund operation security assessment report comprises the target fund security information;

a sending module for uploading the target fund operation security assessment report to the computer device.

In a third aspect, an embodiment of the present invention provides a computer device, where the computer device includes a processor and a non-volatile memory storing computer instructions, and when the computer instructions are executed by the processor, the computer device executes the medical fund data analysis processing method according to the first aspect.

In a fourth aspect, an embodiment of the present invention provides a readable storage medium, where the readable storage medium includes a computer program, and the computer program controls, when running, a computer device where the readable storage medium is located to perform the medical fund data analysis processing method according to the first aspect.

Compared with the prior art, the beneficial effects provided by the invention comprise: the embodiment of the invention provides a medical fund data analysis processing method, a device and a readable storage medium, which are used for acquiring fund service operation data to be graded and analyzed from a fund data server and grading, analyzing and processing the fund service operation data to be graded and analyzed; adding the fund service operation data which is subjected to rating analysis into the fund service knowledge graph, wherein the fund service operation data which is subjected to rating analysis is added into the first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data which is subjected to rating analysis, and in the first fund service knowledge graph, the fund service operation data which is larger in preset safety matching value of the preset fund service reference operation parameters is higher in rating; then, in response to a viewing request for uploading the fund service operation data subjected to rating analysis to the computer equipment, obtaining the fund service operation data subjected to rating analysis from the first fund service knowledge graph, and determining target fund security information according to the obtained fund service operation data subjected to rating analysis; generating a target fund operation safety assessment report, wherein the target fund operation safety assessment report comprises the target fund safety information; and finally, uploading the target fund operation safety evaluation report to the computer equipment, so that the analysis on the safety of the medical fund data can be completed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments will be briefly described below. It is appreciated that the following drawings depict only certain embodiments of the invention and are therefore not to be considered limiting of its scope. For a person skilled in the art, it is possible to derive other relevant figures from these figures without inventive effort.

FIG. 1 is a block diagram schematically illustrating the structure of a medical fund data analysis and processing system according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart illustrating steps of a method for analyzing and processing medical fund data according to an embodiment of the present invention;

fig. 3 is a block diagram schematically illustrating the structure of a medical fund data analysis and processing apparatus according to an embodiment of the present invention;

fig. 4 is a block diagram schematically illustrating a structure of a computer device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. 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.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

Furthermore, the terms "first," "second," and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.

In the description of the present invention, it is also to be noted that, unless otherwise explicitly stated or limited, the terms "disposed" and "connected" are to be interpreted broadly, and for example, "connected" may be a fixed connection, a detachable connection, or an integral connection; can be mechanically or electrically connected; the connection may be direct or indirect via an intermediate medium, and may be a communication between the two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.

The following detailed description of embodiments of the invention refers to the accompanying drawings.

Currently, due to the large number of medical projects and the large amount of required funds, most of the medical projects adopt a fund form as a fund source of the projects so as to be managed. Then, in the existing medical fund management mode, the security of the medical fund data cannot be guaranteed, the situations of wrong account, missed account and even false account can occur, and even because of the huge amount of the medical fund, illegal attack operation can occur. To analyze the security of the medical fund data, please refer to fig. 1, and fig. 1 is an interactive schematic diagram of a medical fund data analysis processing system according to an embodiment of the present invention. The medical fund data analysis processing system may include a computer device 100 and a fund data server 200, the computer device 100 being communicatively connected to the fund data server 200. The medical fund data analysis processing system shown in fig. 1 is only one possible example. In other possible embodiments, the medical fund data analysis and processing system may include only a portion of the components shown in fig. 1 or may also include other component steps.

In this embodiment, the fund data server 200 may comprise a mobile device, a tablet computer, a laptop computer, or the like, or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home devices may include control devices of smart electrical devices, smart monitoring devices, smart televisions, smart cameras, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant, a gaming device, and the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like.

In the embodiment of the present invention, the computer device 100 and the fund data server 200 in the medical fund data analysis processing system may be configured to execute the medical fund data analysis processing method described in the following method embodiment, and the detailed description of the method embodiment may be referred to in the following step section of the execution of the specific computer device 100 and the medical fund data analysis processing system.

To solve the technical problems in the background art, fig. 2 is a schematic flow chart illustrating steps of a medical fund data analysis processing method according to an embodiment of the present invention, in which a fund data server 200 stores a fund service knowledge graph, the fund service knowledge graph includes a first fund service knowledge graph, and the first fund service knowledge graph is used for storing fund service operation data that has been subjected to rating analysis.

Step 201, obtaining the fund service operation data to be rated and analyzed from the fund data server 200, and performing rating analysis processing on the fund service operation data to be rated and analyzed.

Step 202, adding the fund service operation data after rating analysis to the fund service knowledge graph.

The fund service operation data which is subjected to rating analysis is added into a first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data which is subjected to rating analysis, and in the first fund service knowledge graph, the fund service operation data which is larger in preset safety matching value of the preset fund service reference operation parameters is higher in rating.

Step 203, responding to a viewing request for uploading the fund service operation data subjected to rating analysis to the computer device 100, acquiring the fund service operation data subjected to rating analysis from the first fund service knowledge graph, and determining target fund security information according to the fund service operation data subjected to rating analysis.

And step 204, generating a target fund operation safety evaluation report, wherein the target fund operation safety evaluation report comprises target fund safety information.

Step 205, uploading the target fund operation security assessment report to the computer device 100.

The fund service operation data may include, but is not limited to, an initiating operation of the fund service, a transferring operation of the fund service, an ending operation of the fund service, a related account information altering operation in the fund service, and the like. The rating analysis completed fund service operation data may be stored in the first fund service knowledge graph for subsequent processing. The rating standard of the fund service operation data can be determined by the preset security matching value of the preset fund service reference operation parameter related to the rating standard, and the larger the preset security matching value is, the higher the fund service operation data rating is, namely, the safer the fund service operation data rating is. The user may send a request to view fund service operation data, and may determine target fund security information based on the fund service operation data completed through rating analysis, where the target fund security information may refer to an information set that has passed rating and includes medical fund-related operation information, and the generated target fund operation security evaluation report may be a table for sorting and arranging the target fund security information. The target fund operation security assessment report may then be uploaded to the computer device 100 for viewing by the user. The user can analyze the security of the fund service operation data through the target fund operation security assessment report so as to find whether the fund has a leak or not in time.

On the basis, the fund service knowledge graph further comprises a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a first early warning evaluation value, the second fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a second early warning evaluation value, the first early warning evaluation value is a preset safety matching value of preset fund service reference operation parameters obtained when the fund service operation data which is subjected to rating analysis is uploaded, the second early warning evaluation value is determined according to a data source of the fund service operation data which is subjected to rating analysis and received by the computer equipment 100, and the preset fund service reference operation parameters obtained when the fund service operation data which is subjected to rating analysis is uploaded to the computer equipment 100, and the fund service operation data stored in the first fund service knowledge graph is distributed in a descending order according to the first early warning evaluation value from high to low And the fund service operation data stored in the second fund service knowledge graph is distributed in descending order from the high to the low of the second early warning evaluation value. Based on this, as an alternative embodiment, the foregoing step 202 may include the following detailed description.

Sub-step 202-1, adding the rating analyzed fund service operation data to the second fund service knowledge graph.

Accordingly, the foregoing step 203 may include the following detailed description.

Substep 203-1, determining preset rules for obtaining the fund service operation data, for which rating analysis has been completed, from the first fund service knowledge-graph and the second fund service knowledge-graph.

The preset rules comprise a first fund confidence corresponding to the first fund service knowledge graph and a second fund confidence corresponding to the second fund service knowledge graph.

Substep 203-2, a set of fund service operation data objects to be uploaded into the computer device 100 is obtained.

Substep 203-3, determining a first percentage according to the fund service operation data object set and the first fund confidence, and determining a second percentage according to the fund service operation data object set and the second fund confidence.

And a substep 203-4, acquiring fund service operation data with a first ratio from the first fund service knowledge graph according to the sequence of the first early warning evaluation values from high to low as a preset fund service reference operation parameter.

And a substep 203-5, acquiring fund service operation data with a second proportion from the second fund service knowledge graph according to the sequence of the second early warning evaluation values from high to low as fund service operation data to be subjected to rating analysis, and determining target fund safety information according to preset fund service reference operation parameters and the fund service operation data to be subjected to rating analysis.

In embodiments of the present invention, the fund service operational data completed with the rating analysis may also be added to the second fund service knowledge-graph, a predetermined rule may be determined for obtaining the rating analyzed fund service operation data from the first fund service knowledge-graph and the second fund service knowledge-graph, specifically, determining a first proportion according to the fund service operation data object set and the first fund confidence coefficient, determining a second proportion according to the fund service operation data object set and the second fund confidence coefficient, acquiring fund service operation data of the second proportion from the second fund service knowledge graph according to the sequence of the second early warning evaluation value from high to low as fund service operation data to be graded and analyzed, and determining target fund safety information according to the preset fund service reference operation parameters and the fund service operation data to be graded and analyzed. Through the steps, the target fund safety information required by the user can be accurately acquired.

On the basis of the above, the fund service operation data of which the rating analysis is finished is further added to a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing the fund service operation data of which the rating analysis is finished with a first early warning evaluation value, and the second fund service knowledge graph is used for representing the fund service operation data of which the rating analysis is finished with a second early warning evaluation value. The foregoing step 202 also includes the following embodiments.

And a substep 202-2 of obtaining attribute information of the fund service operation data subjected to rating analysis, and determining a first early warning evaluation value and a second early warning evaluation value of the fund service operation data subjected to rating analysis according to the attribute information.

And a substep 202-3 of adding the fund service operation data completed by rating analysis to the first fund service knowledge graph and the second fund service knowledge graph according to the first early warning evaluation value and the second early warning evaluation value of the fund service operation data completed by rating analysis.

In the embodiment of the present invention, when the first early warning evaluation value and the second early warning evaluation value of the fund service operation data are determined according to the attribute information of the fund service operation data subjected to rating analysis, the fund service operation data subjected to rating analysis is added to the first fund service knowledge graph and the second fund service knowledge graph based on the first early warning evaluation value and the second early warning evaluation value, respectively. Through the steps, the fund service operation data can be conveniently added into the first fund service knowledge graph and the second fund service knowledge graph.

To explain the foregoing sub-step 202-2 in more detail, an embodiment of the present invention provides a specific implementation of the foregoing sub-step 202-2.

(1) The preset fund service reference operation parameters obtained when the fund service operation data completed by the rating analysis is uploaded to the computer device 100 are determined, and the data source from which the fund data server 200 receives the fund service operation data completed by the rating analysis is determined.

(2) And determining a first early warning evaluation value of the fund service operation data subjected to rating analysis in the first fund service knowledge graph according to the preset fund service reference operation parameters.

(3) And determining a second early warning evaluation value of the fund service operation data subjected to rating analysis in the second fund service knowledge graph according to the preset fund service reference operation parameters and the data source.

Specifically, the evaluation criterion of the first early warning evaluation value may be determined by a preset fund service reference operating parameter, and may be a type of the preset fund service reference operating parameter, including sensitive types such as transfer, account information change, and the like, and common types such as project initiation, project termination, and the like. The criterion for evaluating the second warning evaluation value may be determined based on the preset fund service reference operation parameter and the data source, for example, the safety factor corresponding to the data source is higher, and the second warning evaluation value is also higher. Through the steps, the first early warning evaluation value and the second early warning evaluation value with higher reference values can be obtained.

On the basis of the above, the embodiment of the present invention provides a specific implementation manner of the foregoing sub-step 202-3, so as to describe the sub-step 202-3 more clearly.

(1) And adding the fund service operation data subjected to rating analysis into the first fund service knowledge graph according to the first early warning evaluation value.

(2) And adding the fund service operation data subjected to rating analysis into the second fund service knowledge graph according to the second early warning evaluation value.

On the basis of the foregoing, the embodiment of the present invention provides a specific implementation manner of the foregoing step 201.

In substep 201-1, fund service operation data appearing in the fund data server 200 is counted to obtain a plurality of fund service operation data.

Substep 201-2, for each fund business operation data of the plurality of fund business operation data, counts the occurrence number of the fund business operation data in the fund data server 200.

And a substep 201-3 of removing the fund service operation data from the plurality of fund service operation data if the occurrence frequency does not reach a first preset operation frequency threshold value.

Substep 201-4, using the plurality of fund service operation data as elements respectively, establishes logical association between fund service operation data appearing in the same fund data server 200 at the same time, so as to establish a logical relationship table between the plurality of fund service operation data.

The logic relation table is used for representing the incidence relation among a plurality of fund service operation data.

And a substep 201-5 of selecting a preset fund service reference operation parameter from the plurality of fund service operation data, and determining a preset security matching value corresponding to the preset fund service reference operation parameter according to the corresponding relationship between the preset fund service reference operation parameter and each preset security level operation.

And a substep 201-6, for each fund business operation data to be rated and analyzed, respectively determining the correlation between the fund business operation data to be rated and each fund business operation data adjacent to the fund business operation data to be rated and analyzed according to the weight of each logic association connected with the fund business operation data to be rated and analyzed.

And a substep 201-7 of determining a preset security matching value of the fund business operation data to be rated and analyzed according to the correlation between the fund business operation data to be rated and each fund business operation data adjacent to the fund business operation data and the preset security matching value of each fund business operation data adjacent to the fund business operation data.

The preset security matching value corresponding to the preset fund service reference operation parameter and the preset security matching value corresponding to the fund service operation data to be subjected to rating analysis are respectively a security object data set, the number of the security object data in the security object data set is the same as the number of the preset security level operations, and the security object data in the security object data set respectively represent the probability that the preset fund service reference operation parameter and the fund service operation data to be subjected to rating analysis respectively belong to each preset security level operation.

And a substep 201-8 of determining the security object data with the maximum value in the preset security matching values corresponding to the fund service operation data to be subjected to rating analysis, and determining the preset security level operation corresponding to the security object data with the maximum value.

And a substep 201-9, determining the fund service operation data to be rated and analyzed as the fund service operation data to be rated and analyzed corresponding to the preset security level operation, so as to finish rating analysis processing on the fund service operation data to be rated and analyzed.

The fund service operation data appearing in the fund data server 200 may be counted first, and the fund service operation data that does not reach the standard may be removed according to whether the appearing number reaches the first preset operation number threshold, so as to ensure the reliability of the data. A logical relationship table among a plurality of fund business operation data can be established, and the correlation between the fund business operation data to be evaluated and each fund business operation data adjacent to the fund business operation data can be respectively determined based on the weight of the logical association in the logical relationship table. Then determining the preset safe matching value of the fund service operation data to be graded and analyzed according to the correlation between the fund service operation data to be graded and the fund service operation data adjacent to the fund service operation data and the preset safe matching value of the fund service operation data adjacent to the fund service operation data, the security object data with the maximum value in the preset security matching values corresponding to the fund service operation data to be rated and analyzed can be determined, determining the preset security level operation corresponding to the security object data with the largest value, determining the fund service operation data to be rated and analyzed as the fund service operation data to be rated and analyzed corresponding to the preset security level operation so as to finish rating analysis processing on the fund service operation data to be rated and analyzed, through the steps, reliable fund service operation data used for the to-be-evaluated analysis corresponding to the preset security level operation serving as the security reference basis can be obtained.

In addition to the above steps, in an embodiment of the present invention, before step 202, the method further includes:

step 206, obtain a set of fund service operation data objects in the first fund service knowledge-graph and a set of fund service operation data objects in the second fund service knowledge-graph.

Based on step 206, embodiments of the present invention also employ another embodiment of step 202.

Substep 202-4, adding the rating analyzed fund service operation data to the first fund service knowledge-graph when the set of fund service operation data objects in the first fund service knowledge-graph is less than or equal to the set of fund service operation data objects in the second fund service knowledge-graph.

Through the steps, the fund service operation data object set in the first fund service knowledge graph can be further optimized based on the fund service operation data object set in the second fund service knowledge graph, so that the data in the first fund service knowledge graph has reasonable referential property. In contrast, step 202 may further include:

substep 202-5, storing the rating analyzed fund service operation data into the second fund service knowledge-graph when the fund service operation data object set in the first fund service knowledge-graph is greater than the fund service operation data object set in the second fund service knowledge-graph.

In addition to the above steps, an embodiment of the present invention further provides a scheme for adjusting the confidence level of the first fund and the confidence level of the second fund according to the set of fund service operation data objects in the first fund service knowledge-graph and the set of fund service operation data objects in the second fund service knowledge-graph, which may specifically include the following implementation manners.

Step 301, when it is detected that the fund service operation data object set in the first fund service knowledge-graph is increased and the fund service operation data object set in the second fund service knowledge-graph is decreased, increasing the first fund confidence level and decreasing the second fund confidence level.

Step 302, when it is detected that the set of fund service operation data objects in the first fund service knowledge-graph decreases and the set of fund service operation data objects in the second fund service knowledge-graph increases, decreasing the first fund confidence level and increasing the second fund confidence level.

As an alternative embodiment, the preset fund service reference operation parameter and the fund service operation data to be graded and analyzed are respectively in a plurality of proportions. Prior to the foregoing step 204, the following implementation manner is also provided in the embodiment of the present invention.

And determining repeated fund service operation data from the preset fund service reference operation parameters, wherein the repeated fund service operation data is fund service operation data which is acquired from the first fund service knowledge graph and acquired from the second fund service knowledge graph.

Deleting the duplicate fund service operation data obtained from the first fund service knowledge-graph or deleting the duplicate fund service operation data obtained from the second fund service knowledge-graph.

The embodiment of the invention provides a medical fund data analysis processing device which is applied to computer equipment 100, wherein the computer equipment 100 is in communication connection with a fund data server 200, the fund data server 200 stores a fund service knowledge graph, and the fund service knowledge graph comprises a first fund service knowledge graph which is used for storing fund service operation data which is subjected to rating analysis. As shown in fig. 3, the medical fund data analysis processing apparatus includes:

the obtaining module 1101 is configured to obtain the fund service operation data to be rating-analyzed from the fund data server 200, and perform rating analysis processing on the fund service operation data to be rating-analyzed.

An adding module 1102, configured to add the fund service operation data subjected to rating analysis to a fund service knowledge graph, where the fund service operation data subjected to rating analysis is added to a first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data subjected to rating analysis, and in the first fund service knowledge graph, the larger the preset security matching value of the preset fund service reference operation parameters is, the higher the ranking of the fund service operation data is.

A response module 1103, configured to, in response to the viewing request for uploading the fund service operation data completed with the rating analysis to the computer device 100, obtain the fund service operation data completed with the rating analysis from the first fund service knowledge graph, and determine target fund security information according to the obtained fund service operation data completed with the rating analysis.

A generating module 1104, configured to generate a target fund operation security assessment report, where the target fund operation security assessment report includes target fund security information.

A sending module 1105 configured to upload the target fund operation security assessment report to the computer device 100.

Further, the fund service knowledge graph further comprises a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a first early warning evaluation value, the second fund service knowledge graph is used for representing fund service operation data which is subjected to rating analysis by using a second early warning evaluation value, the first early warning evaluation value is a preset safety matching value of a preset fund service reference operation parameter obtained when the fund service operation data which is subjected to rating analysis is uploaded, the second early warning evaluation value is a data source according to the fund service operation data which is subjected to rating analysis and received by the computer device 100, the fund service operation data which is subjected to rating analysis is uploaded to the computer device 100, the preset fund service reference operation parameter obtained when the fund service operation data which is subjected to rating analysis is uploaded, the fund service operation data which is stored in the first fund service knowledge graph is distributed in descending order according to the first early warning evaluation value, the fund service operation data stored in the second fund service knowledge graph are distributed in a descending order from the high to the low of the second early warning evaluation value;

the adding module 1102 is specifically configured to:

and adding the fund service operation data after rating analysis is completed to the second fund service knowledge graph.

The response module 1103 is specifically configured to:

determining a preset rule for acquiring fund service operation data which is subjected to rating analysis from the first fund service knowledge graph and the second fund service knowledge graph, wherein the preset rule comprises a first fund confidence corresponding to the first fund service knowledge graph and a second fund confidence corresponding to the second fund service knowledge graph; acquiring a fund service operation data object set to be uploaded to the computer device 100; determining a first proportion according to the fund service operation data object set and the first fund confidence coefficient, and determining a second proportion according to the fund service operation data object set and the second fund confidence coefficient; acquiring fund service operation data with a first proportion from a first fund service knowledge graph according to the sequence of a first early warning evaluation value from high to low as a preset fund service reference operation parameter; and acquiring fund service operation data with a second proportion from the second fund service knowledge graph according to the sequence of the second early warning evaluation value from high to low as fund service operation data to be rated and analyzed, and determining target fund safety information according to preset fund service reference operation parameters and the fund service operation data to be rated and analyzed.

Further, the fund service operation data which is subjected to rating analysis is added into a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing the fund service operation data which is subjected to rating analysis by a first early warning evaluation value, and the second fund service knowledge graph is used for representing the fund service operation data which is subjected to rating analysis by a second early warning evaluation value;

the adding module 1102 is specifically configured to:

acquiring attribute information of the fund service operation data subjected to rating analysis, and determining a first early warning evaluation value and a second early warning evaluation value of the fund service operation data subjected to rating analysis according to the attribute information; and adding the fund service operation data subjected to rating analysis into the first fund service knowledge graph and the second fund service knowledge graph according to the first early warning evaluation value and the second early warning evaluation value of the fund service operation data subjected to rating analysis.

Further, the adding module 1102 is further specifically configured to:

determining preset fund service reference operation parameters acquired when the fund service operation data subjected to rating analysis is uploaded to the computer device 100, and determining a data source of the fund service operation data subjected to rating analysis received by the fund data server 200; determining a first early warning evaluation value of fund service operation data which is subjected to rating analysis in a first fund service knowledge graph according to preset fund service reference operation parameters; and determining a second early warning evaluation value of the fund service operation data subjected to rating analysis in the second fund service knowledge graph according to the preset fund service reference operation parameters and the data source.

Further, the adding module 1102 is further specifically configured to:

adding fund service operation data subjected to rating analysis into the first fund service knowledge graph according to the first early warning evaluation value; and adding the fund service operation data subjected to rating analysis into the second fund service knowledge graph according to the second early warning evaluation value.

The obtaining module 1101 is specifically configured to:

the fund service operation data appearing in the fund data server 200 is counted to obtain a plurality of fund service operation data; counting the occurrence times of the fund service operation data in the fund data server 200 aiming at each fund service operation data in the plurality of fund service operation data; removing the fund service operation data from the plurality of fund service operation data if the occurrence frequency does not reach a first preset operation frequency threshold value; respectively taking a plurality of fund service operation data as elements, and establishing logical association among fund service operation data which simultaneously appear in the same fund data server 200 so as to establish a logical relationship table among the plurality of fund service operation data, wherein the logical relationship table is used for representing the association relationship among the plurality of fund service operation data; selecting a preset fund service reference operation parameter from the plurality of fund service operation data, and determining a preset safety matching value corresponding to the preset fund service reference operation parameter according to the corresponding relation between the preset fund service reference operation parameter and each preset safety level operation; for each fund service operation data to be rated and analyzed, respectively determining the correlation between the fund service operation data to be rated and analyzed and each fund service operation data adjacent to the fund service operation data to be rated and analyzed according to the weight of each logic association connected with the fund service operation data to be rated and analyzed; determining a preset security matching value of the fund service operation data to be graded and analyzed according to the correlation between the fund service operation data to be graded and each fund service operation data adjacent to the fund service operation data to be graded and the preset security matching value of each fund service operation data adjacent to the fund service operation data to be graded and analyzed, wherein the preset security matching value corresponding to the preset fund service reference operation parameter and the preset security matching value corresponding to the fund service operation data to be graded and analyzed are respectively a security object data set, the number of security object data in the security object data set is the same as the number of preset security level operations, and the security object data in the security object data set respectively represent the probability that the preset fund service reference operation parameter and the fund service operation data to be graded and analyzed respectively belong to each preset security level operation; determining the safety object data with the maximum value in the preset safety matching values corresponding to the fund service operation data to be graded and analyzed, and determining the preset safety level operation corresponding to the safety object data with the maximum value; and determining the fund service operation data to be rated and analyzed as the fund service operation data to be rated and analyzed corresponding to the preset security level operation so as to finish rating analysis processing on the fund service operation data to be rated and analyzed.

The obtaining module 1101 is further configured to:

a set of fund service operation data objects in the first fund service knowledge graph and a set of fund service operation data objects in the second fund service knowledge graph are obtained.

The adding module 1102 is specifically further configured to:

It should be noted that, for the implementation principle of the medical fund data analysis and processing device, reference may be made to the implementation principle of the medical fund data analysis and processing method, which is not described herein again. It should be understood that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the obtaining module 1101 may be a processing element separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the processing element of the apparatus calls and executes the functions of the obtaining module 1101. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

The embodiment of the invention provides a computer device 100, wherein the computer device 100 comprises a processor and a nonvolatile memory storing computer instructions, and when the computer instructions are executed by the processor, the computer device 100 executes the medical fund data analysis processing method. As shown in fig. 4, fig. 4 is a block diagram of a computer device 100 according to an embodiment of the present invention. The computer apparatus 100 includes a medical fund data analysis processing device, a memory 111, a processor 112, and a communication unit 113.

To facilitate the transfer or interaction of data, the elements of the memory 111, the processor 112 and the communication unit 113 are electrically connected to each other, directly or indirectly. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The medical fund data analysis processing apparatus includes at least one software function module which may be stored in the memory 111 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the computer device 100. The processor 112 is configured to execute a generation module 1104 stored in the memory 111, for example, a software function module and a computer program included in the medical fund data analysis processing apparatus.

The embodiment of the invention provides a readable storage medium, which includes a computer program, and when the computer program runs, the computer device 100 where the readable storage medium is located is controlled by the computer program to execute the aforementioned medical fund data analysis processing method.

In summary, embodiments of the present invention provide a method, an apparatus, and a readable storage medium for analyzing and processing medical fund data, in which fund service operation data to be rated and analyzed is obtained from a fund data server, and the fund service operation data to be rated and analyzed is subjected to rating analysis; adding the fund service operation data which is subjected to rating analysis into the fund service knowledge graph, wherein the fund service operation data which is subjected to rating analysis is added into the first fund service knowledge graph, the first fund service knowledge graph is constructed according to preset fund service reference operation parameters related to the fund service operation data which is subjected to rating analysis, and in the first fund service knowledge graph, the fund service operation data which is larger in preset safety matching value of the preset fund service reference operation parameters is higher in rating; then, in response to a viewing request for uploading the fund service operation data subjected to rating analysis to the computer equipment, obtaining the fund service operation data subjected to rating analysis from the first fund service knowledge graph, and determining target fund security information according to the obtained fund service operation data subjected to rating analysis; generating a target fund operation safety assessment report, wherein the target fund operation safety assessment report comprises the target fund safety information; and finally, uploading the target fund operation safety evaluation report to the computer equipment, so that the analysis on the safety of the medical fund data can be completed.

The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. Many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosure and various embodiments with various modifications as are suited to the particular use contemplated. The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. Many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosure and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A medical fund data analysis and processing method is characterized by being applied to computer equipment which is in communication connection with a fund data server, wherein a fund service knowledge graph is stored in the fund data server and comprises a first fund service knowledge graph, and the first fund service knowledge graph is used for storing fund service operation data which is subjected to rating analysis;

the method comprises the following steps:

2. The method of claim 1, wherein the fund service knowledge-graph further comprises a second fund service knowledge-graph, wherein the first fund service knowledge-graph is used for representing fund service operation data of which the rating analysis is completed by a first early warning evaluation value, the second fund service knowledge-graph is used for representing fund service operation data of which the rating analysis is completed by a second early warning evaluation value, the first early warning evaluation value is a preset safety matching value of preset fund service reference operation parameters obtained when the fund service operation data of which the rating analysis is completed is uploaded, the second early warning evaluation value is determined according to a data source of the fund service operation data of which the rating analysis is completed and the preset fund service reference operation parameters obtained when the fund service operation data of which the rating analysis is completed is uploaded to the computer device, fund service operation data stored by the first fund service knowledge graph is distributed in descending order from the first early warning evaluation value to low, and fund service operation data stored by the second fund service knowledge graph is distributed in descending order from the second early warning evaluation value to high;

3. The method of claim 1, wherein the rating analysis completed fund service operation data is further added to a second fund service knowledge graph, wherein the first fund service knowledge graph is used for representing rating analysis completed fund service operation data with a first early warning assessment value, and the second fund service knowledge graph is used for representing rating analysis completed fund service operation data with a second early warning assessment value;

4. The method of claim 3, wherein the determining the first warning evaluation value and the second warning evaluation value of the fund service operation data after the rating analysis is completed according to the attribute information comprises:

5. The method of claim 4, wherein adding the rating analysis completed fund service operation data to the first fund service knowledge-graph and the second fund service knowledge-graph according to the first early warning rating value and the second early warning rating value of the rating analysis completed fund service operation data comprises:

6. The method of claim 1, wherein the step of rating analyzing the fund service operation data to be rated comprises:

7. The method according to claim 2, wherein prior to the step of adding ratings analysis completed fund service operation data to the fund service knowledge-graph, the method further comprises:

8. A medical fund data analysis and processing device is applied to computer equipment which is in communication connection with a fund data server, wherein the fund data server stores a fund service knowledge graph, the fund service knowledge graph comprises a first fund service knowledge graph, and the first fund service knowledge graph is used for storing fund service operation data which is subjected to rating analysis;

the device comprises:

9. A computer device comprising a processor and a non-volatile memory storing computer instructions that, when executed by the processor, perform the medical fund data analysis processing method of any one of claims 1 to 7.

10. A readable storage medium, characterized in that the readable storage medium comprises a computer program which, when executed, controls a computer device on which the readable storage medium is located to perform the medical fund data analysis processing method according to any one of claims 1 to 7.