Multi-process data integration traceability supervision system and method based on cloud service

Abstract

The invention discloses a multi-process data integration traceability supervision system and method based on cloud service, and relates to the technical field of data traceability supervision, and the method comprises the steps: evaluating rejection factors in the examination and approval process of an examination and approval institution and the influence degree on business applied by an enterprise, and obtaining target rejection data; obtaining a business application material uploaded by the enterprise in the application assistance platform, obtaining target rejection data, evaluating the business rejection risk of the business application material in the approval process of the approval agency, and obtaining target risk data; obtaining a historical application process record of the enterprise, tracing a business application process in the enterprise in combination with the target risk data, identifying a root cause affecting business application of the enterprise, and obtaining target abnormal data; and obtaining target abnormal data, generating business application suggestion data of the enterprise, pushing the business application suggestion data to the enterprise, carrying out application process supervision on the enterprise, and assisting the enterprise to carry out business application to an approval agency.

Description

Technical Field

[0001] The present invention relates to the technical field of data traceability supervision, and specifically to a multi-process data integration traceability supervision system and method based on cloud services. Background Art

[0002] In the normal business application of enterprises, it is necessary to involve multiple departments such as industry and commerce, taxation, banking, and environmental protection. Moreover, the data formats involved in the project application process are diverse (including unstructured documents, structured tables, etc.). The cloud service technology can centrally store multi-source data through a cloud-native database and support various storage methods. Therefore, as an emerging technology, cloud services have been gradually applied to the business applications of enterprises. When facing policy adjustments and business expansions, traditional technologies need to frequently modify processes. Cloud services can use cloud-native technologies such as Kubernetes to quickly deploy new process nodes without physical server expansion, overcoming the shortcoming of the risk of single-point tampering in traditional centralized systems. In addition, cloud services can also use the integrated blockchain to build a centralized traceability chain to ensure that the operation records during the business application process of enterprises cannot be tampered with, and at the same time avoid the high hardware costs and operation and maintenance costs required for self-built data centers, saving the cost expenditure during the business application process.

[0003] In real life, different enterprises need to apply for different businesses, and there are also different approval agencies for business approvals. Different approval agencies have different requirements for business applications. Once an enterprise submits application materials, it is very difficult to modify the submitted materials on a large scale. Even if modifications can be made, they can only be made to small-scale errors. However, modifications still need to be applied to the approval agency. But the existing solutions are difficult to trace each link in the enterprise's business application materials according to the requirements of different approval agencies, and solve the problems existing in the enterprise's application materials from the source. This not only makes it difficult to supervise the business application materials, but also causes enterprises to waste application opportunities, seriously affecting the business development and normal operation of enterprises. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-process data integration traceability supervision system and method based on cloud services to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: A multi-process data integration traceability supervision method based on cloud services, the method includes:

[0006] Step S100: Obtain the historical application rejection records in the approval agencies for the enterprise's business application, obtain the rejection factors of the characteristic rejection data in the enterprise's application assistance platform, evaluate the impact degree of the rejection factors on the enterprise's applied business during the approval process of the approval agency, and obtain the target rejection data;

[0007] Step S200: Obtain the business application materials uploaded by the enterprise in the application assistance platform, obtain the target rejection data, evaluate the business rejection risk of the business application materials during the approval process of the approval agency, and obtain the target risk data;

[0008] Step S300: Obtain the historical application process records of the enterprise, and in combination with the target risk data, trace the business application process in the enterprise, identify the root causes affecting the enterprise's business application, and obtain the target abnormal data;

[0009] Step S400: Obtain the target abnormal data, generate the business application suggestion data for the enterprise, push it to the enterprise, and conduct supervision on the enterprise's application process to assist the enterprise in applying for business to the approval agency.

[0010] Further, Step S100 includes:

[0011] Step S101: Obtain the approval agencies that approve the enterprise's applied business, obtain each historical application rejection record in the approval agency from the pre-constructed application assistance platform, and obtain the historical rejection text from the historical application rejection records;

[0012] Step S102: Obtain the characteristic rejection data in the application assistance platform, where the characteristic rejection data includes the text content corresponding to each preset rejection factor in the application assistance platform;

[0013] Perform text preprocessing on the historical rejection text, and based on the preset sentence splitting model, split the historical rejection text into sentences, obtain each sentence in the historical rejection text, and gather them to obtain the sentence set in the historical rejection text;

[0014] Step S103: Use the pre-constructed sentence vector model in the application assistance platform to obtain the characteristic vectors corresponding to each sentence in the sentence set. Based on the text content corresponding to each rejection factor in the application assistance platform, and in combination with the sentence splitting model and the sentence vector model, obtain the sentence vector set of each rejection factor;

[0015] Obtain the characteristic vector of a certain sentence in the historical rejection text, obtain the maximum value R of the cosine similarity between a certain sentence and each element in the sentence vector set of each rejection factor max and obtain the maximum value R max when, a certain rejection factor corresponding to a certain sentence;

[0016] Step S104: When the maximum value R of the cosine similarity max is greater than the preset similarity threshold, determine that a certain sentence is the characteristic sentence of a certain rejection factor;

[0017] Step S105: Obtain the sum A of the total number of characteristic sentences of each rejection factor in the historical rejection text sum , calculate the characteristic influence value B' of a certain rejection factor in the historical application rejection record: B' = A' sum / A sum , where A' sum is the total number of characteristic sentences in the historical rejection text in the historical application rejection record of a certain rejection factor;

[0018] When the characteristic influence value B' is greater than the preset characteristic influence threshold, record the historical application rejection record as the marked historical application rejection record of a certain rejection factor;

[0019] Calculate the rejection influence value C' of a certain rejection factor in the approval process of the approval agency on the enterprise's application business:

[0020]

[0021] where j is the total number of each historical application rejection record; B' i is the characteristic influence value of the i-th historical application rejection record of a certain rejection factor in the approval agency;

[0022] Step S106: When the rejection influence value C' is greater than the preset rejection influence threshold, determine that a certain rejection factor in the approval process of the approval agency has an impact on the rejection of the enterprise's application business, and record a certain rejection factor as the target rejection factor;

[0023] Obtain each target rejection factor in the review agency, obtain the marked historical application rejection records of each target rejection factor, and perform aggregation to obtain the target rejection data.

[0024] Furthermore, step S200 includes:

[0025] Step S201: Obtain the business application materials uploaded by the enterprise in the application assistance platform, and obtain the application texts corresponding to each material category from the business application materials;

[0026] Step S202: Obtain the target rejection data of the approval agency, obtain each target rejection factor from the target rejection data, obtain the marked historical application rejection records corresponding to each target rejection factor, and obtain the historical application texts corresponding to each material category from the marked historical application rejection records;

[0027] Step S203: Evaluate the business rejection risk during the approval process of business application materials. The specific evaluation process is as follows:

[0028] Obtain the application text D corresponding to a certain material category in the business application materials, and obtain the historical application text F of a certain material category in a certain marked application rejection record corresponding to a certain target rejection factor;

[0029] Divide the application text D and the historical application text F into text blocks respectively, and use a text conversion tool to convert a certain text block in the application file D and another historical text block in the historical application file F into several strings and gather them to obtain the file string set D' and the historical file string set F';

[0030] Step S204: Create a two-dimensional array H, and obtain the element H[x][y] in the x-th row and y-th column of the two-dimensional array, where source[x] is the string in the historical file string set F', and source[y] is the string in the file string set D';

[0031] When source[y] = source[x], H[x][y] = H[x - 1][y - 1]; when source[x] = 0, H[0][y] = y; when source[y] = 0, H[x][0] = x; when source[y] ≠ source[x], H[x][y] = {1 + min{H[x - 1][y], H[x][y - 1], H[x - 1][y - 1]}};

[0032] Obtain the last element H[m][n] in the lower right corner of the two-dimensional array H, where n represents the total number of strings in the file string set D', and m represents the total number of strings in the historical file string set F', and calculate the text block similarity value R' between a certain text block and another historical text block (d，f) :

[0033]

[0034] Obtain the maximum value of the text block similarity values between a certain text block and several text blocks in the historical application file F, and record it as the characteristic text block similarity value between a certain text block and the historical application file F;

[0035] Obtain the average value of the characteristic text similarity values between several text blocks in the application text D and the historical application file F, and record it as the text similarity value Q between the application text D and the historical application file F (d,f) ;

[0036] When the text similarity value Q (d,f)If it is greater than the preset text similarity threshold, it is determined that there is a risk that the business application materials are rejected due to a certain target rejection factor. Mark a certain type of material as a risk material category, obtain a certain target rejection factor, and record it as the risk target rejection factor of the risk material category.

[0037] Step S205: When the business application materials contain risk material categories, it is determined that there is a risk of business rejection during the approval process of the approval agency.

[0038] Obtain the risk target rejection factors corresponding to several risk material categories of the business application materials and aggregate them to obtain the target risk data.

[0039] Furthermore, step S300 includes:

[0040] Step S301: Obtain the historical application process records of the business application materials in the enterprise, and from the application process records, obtain the process departments related to each type of material in the business application materials.

[0041] Step S302: Trace the business application process in the enterprise to identify the root causes affecting the enterprise's business application. The specific tracing process is as follows:

[0042] Obtain the target risk data of each business application material in the enterprise during the current period, and obtain the risk material categories in each business application material.

[0043] Step S303: When a certain process department is the process department related to several risk material categories in a certain business application material, obtain the total number of several risk material categories and record it as the characteristic anomaly value of a certain process department in a certain business application material.

[0044] Obtain the abnormal process departments of each target risk material category in each business application material, and calculate the application impact value of each process department responsible for business application in the enterprise. Among them, the application impact value Uk of the kth process department in the enterprise k :

[0045]

[0046] where s is the total number of all business application materials; P k (z,sum) is the characteristic anomaly value of the kth process department in the zth business application material among all business application materials.

[0047] Step S304: When the application impact value U kIf it is greater than the preset business application impact threshold, it is determined that the k-th process department is the root cause affecting the enterprise's business application, and the k-th process department is recorded as an abnormal process department. Each abnormal process department of the enterprise is obtained and aggregated to obtain the target abnormal data of the enterprise.

[0048] Further, step S400 includes:

[0049] Step S401: Obtain the target abnormal data of the enterprise, obtain each abnormal process department from the target abnormal data, and obtain the target risk data of each business application material of the enterprise in the current cycle;

[0050] Step S402: Obtain the risk target rejection factors corresponding to the risk material categories from the target risk data, obtain several risk target rejection factors corresponding to the risk material categories related to a certain abnormal process department, and based on the work log of a certain abnormal process department, obtain the solutions corresponding to several risk target rejection factors from the application assistance platform to obtain the application advice data of a certain process department in the enterprise, and push it to the person in charge of the department of a certain process department;

[0051] Supervise the enterprise in the process of preparing business application materials, and assist the enterprise in applying for business to the approval agency. The specific process is as follows:

[0052] When none of the material categories in the business application materials of the enterprise are marked as risk material categories again, it is determined that the business application materials of the enterprise are allowed to be submitted to the approval agency, otherwise, continue to modify the business application materials until none of the material categories in the business application materials are marked as risk material categories;

[0053] The above steps supervise the enterprise in the process of preparing business application materials, assist the enterprise in applying for business to the approval agency, ensure that the business application materials in the enterprise can be successfully approved by the approval agency, and greatly improve the probability of the business application materials passing smoothly.

[0054] In order to better implement the above method, a multi-process data integration traceability supervision system based on cloud services is also proposed. The system includes a rejection factor evaluation module, a rejection risk evaluation module, a cause traceability module, and an intelligent supervision module;

[0055] The rejection factor evaluation module is used to evaluate the impact degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise to obtain the target rejection data;

[0056] The rejection risk evaluation module is used to evaluate the business rejection risk of the business application materials in the approval process of the approval agency to obtain the target risk data;

[0057] A cause tracing module, which is used to trace the business application process in an enterprise, identify the root causes affecting the enterprise's business application, and obtain target abnormal data;

[0058] An intelligent supervision module, which is used to push the generated business application suggestion data of the enterprise to the enterprise, supervise the application process of the enterprise, and assist the enterprise in applying for business to the approval agency.

[0059] Further, the rejection factor evaluation module includes a rejection impact value unit and a rejection factor evaluation unit;

[0060] The rejection impact value unit is used to calculate the rejection factors in the approval process of the approval agency and the rejection impact value on the enterprise's business application;

[0061] The rejection factor evaluation unit is used to evaluate the impact degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise according to the rejection impact value, and obtain the target rejection data.

[0062] Further, the rejection risk assessment module includes a data acquisition unit and a rejection risk assessment unit;

[0063] The data acquisition unit is used to acquire the business application materials uploaded by the enterprise in the application assistance platform and obtain the historical application texts corresponding to each material category from the historical application rejection records of the approval agency;

[0064] The rejection risk assessment unit is used to evaluate the business rejection risk of the business application materials in the approval process of the approval agency and obtain the target risk data.

[0065] Further, the cause tracing module includes an application impact value unit and a cause tracing unit;

[0066] The application impact value unit is used to calculate the application impact values of each process department responsible for the enterprise's business application;

[0067] The cause tracing unit is used to trace the business application process in the enterprise according to the application impact value, identify the root causes affecting the enterprise's business application, and obtain the target abnormal data of the enterprise.

[0068] Further, the intelligent supervision module includes an intelligent supervision unit;

[0069] The intelligent supervision unit is used to obtain the target abnormal data of the enterprise, obtain the solutions corresponding to several risk target rejection factors from the application assistance platform, obtain the application suggestion data of a certain process department in the enterprise, and push it to the person in charge of the department of a certain process department, and conduct intelligent supervision on the enterprise in the process of preparing business application materials.

[0070] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention realizes intelligent assistance for enterprise business applications. Considering that different approval agencies have different review styles for applications in practice, therefore, starting from the approval agencies where enterprises actually need to apply for business, by analyzing the rejection situations of historical application rejection records in the approval agencies, historical application documents in the historical rejection records with the review characteristics of the approval agencies are obtained, and based on this, the rejection risk in the enterprise's business application process is evaluated. When there is a risk of rejection for a business, the application process in the enterprise is traced back, the root cause in the business application is identified, and the enterprise's business application process is optimized to assist the enterprise in applying for business, greatly improving the success rate of the enterprise in business applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 is a method flow chart of a multi-process data integration traceability supervision system and method based on cloud services according to the present invention;

[0072] Figure 2 is a module schematic diagram of a multi-process data integration traceability supervision system and method based on cloud services according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0073] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0074] Embodiment: As Figure 1 - Figure 2 shown, the present invention provides a technical solution, a multi-process data integration traceability supervision method based on cloud services, and the method includes:

[0075] Step S100: Obtain the historical application rejection records in the approval agency for the enterprise's business application, obtain the rejection factors of the characteristic rejection data in the enterprise's application assistance platform, evaluate the influence degree of the rejection factors on the business applied by the enterprise during the approval process of the approval agency, and obtain the target rejection data;

[0076] Among them, step S100 includes:

[0077] Step S101: Obtain the approval agency that approves the business applied by the enterprise, obtain each historical application rejection record in the approval agency from the pre-constructed application assistance platform, and obtain the historical rejection text from the historical application rejection record;

[0078] Step S102: Obtain the feature rejection data in the application assistance platform. The feature rejection data includes the text content corresponding to each preset rejection factor in the application assistance platform;

[0079] For example, each rejection factor includes missing materials, format errors, etc.;

[0080] Perform text preprocessing on the historical rejection text, and based on the preset sentence splitting model, split the historical rejection text into sentences, obtain each sentence in the historical rejection text, and gather them to obtain the sentence set in the historical rejection text;

[0081] For example, text preprocessing includes text cleaning and standardization;

[0082] Step S103: Use the pre-constructed sentence vector model in the application assistance platform to obtain the feature vectors corresponding to each sentence in the sentence set. Based on the text content corresponding to each rejection factor in the application assistance platform, and in combination with the sentence splitting model and the sentence vector model, obtain the sentence vector set of each rejection factor;

[0083] Obtain the feature vector of a certain sentence in the historical rejection text, and obtain the maximum value R of the cosine similarity between a certain sentence and each element in the sentence vector set of each rejection factor max , and obtain the maximum value R max When, a certain rejection factor corresponding to a certain sentence;

[0084] Step S104: When the maximum value R of the cosine similarity max is greater than the preset similarity threshold, determine that a certain sentence is a feature sentence of a certain rejection factor;

[0085] Step S105: Obtain the sum A of the total number of feature sentences of each rejection factor in the historical rejection text sum , calculate the feature influence value B' of a certain rejection factor in the historical application rejection record = A' sum / A sum , A' sum is the total number of feature sentences in the historical rejection text of a certain rejection factor in the historical application rejection record;

[0086] When the feature influence value B' is greater than the preset feature influence threshold, record the historical application rejection record as the marked historical application rejection record of a certain rejection factor;

[0087] Calculate the rejection influence value C' of a certain rejection factor in the approval process of the approval agency on the enterprise's application business:

[0088]

[0089] where j is the total number of all historical application rejection records; B′ i is the characteristic influence value of the i-th historical application rejection record of a certain rejection factor in the approval agency;

[0090] Step S106: When the rejection influence value C′ is greater than the preset rejection influence threshold, it is determined that a certain rejection factor in the approval process of the approval agency has an impact on the rejection of the business applied by the enterprise, and a certain rejection factor is recorded as the target rejection factor;

[0091] Obtain each target rejection factor in the review agency, obtain the marked historical application rejection records of each target rejection factor, and conduct aggregation to obtain target rejection data;

[0092] Step S200: Obtain the business application materials uploaded by the enterprise in the application assistance platform, obtain the target rejection data, and evaluate the business rejection risk of the business application materials in the approval process of the approval agency to obtain target risk data;

[0093] Among them, Step S200 includes:

[0094] Step S201: Obtain the business application materials uploaded by the enterprise in the application assistance platform, and obtain the application texts corresponding to each material category from the business application materials;

[0095] For example, each material category includes technical documents, project documents, enterprise information, business licenses, etc.;

[0096] Step S202: Obtain the target rejection data of the approval agency, obtain each target rejection factor from the target rejection data, obtain the marked historical application rejection records corresponding to each target rejection factor, and obtain the historical application texts corresponding to each material category from the marked historical application rejection records;

[0097] Step S203: Evaluate the business rejection risk of the business application materials in the approval process of the approval agency. The specific evaluation process is as follows:

[0098] Obtain the application text D corresponding to a certain material category in the business application materials, and obtain the historical application text F of a certain material category in a certain marked application rejection record corresponding to a certain target rejection factor;

[0099] Respectively divide the application text D and the historical application text F into text blocks, and use a text conversion tool to respectively convert a certain text block in the application file D and another historical text block in the historical application file F into several strings and conduct aggregation to obtain a file string set D′ and a historical file string set F′;

[0100] For example, text conversion tools include Notepad, Sublime Text, and VS Code;

[0101] Step S204: Create a two-dimensional array H, and obtain the element H[x][y] at the x-th row and y-th column in the two-dimensional array, where source[x] is the string in the historical file string set F′, and source[y] is the string in the file string set D′;

[0102] When source[y] = source[x], H[x][y] = H[x - 1][y - 1]; when source[x] = 0, H[0][y] = y; when source[y] = 0, H[x][0] = x; when source[y] ≠ source[x], H[x][y] = {1 + min{H[x - 1][y], H[x][y - 1], H[x - 1][y - 1]}};

[0103] Obtain the last element H[m][n] in the lower right corner of the two-dimensional array H, where n represents the total number of strings in the file string set D′, and m represents the total number of strings in the historical file string set F′, and calculate the text block similarity value R′ between a certain text block and another historical text block (d，f) :

[0104]

[0105] Obtain the maximum value of the text block similarity values between a certain text block and several text blocks in the historical application file F, and denote it as the characteristic text block similarity value between the certain text block and the historical application file F;

[0106] For example, if H[m][n] is 4, m is 8, and n is 7, calculate the text block similarity value R′ between a certain text block and another historical text block (d，f) :

[0107]

[0108] Obtain the average value of the characteristic text similarity values between several text blocks in the application text D and the historical application file F, and denote it as the text similarity value Q between the application text D and the historical application file F (d,f) ;

[0109] When the text similarity value Q (d,f) is greater than the preset text similarity threshold, it is determined that there is a risk that the business application materials are rejected due to a certain target rejection factor. Denote a certain material category as the risk material category, and obtain a certain target rejection factor, and denote it as the risk target rejection factor of the risk material category;

[0110] Step S205: When the business application materials contain risk material categories, it is determined that there is a risk of business rejection during the approval process by the approval agency;

[0111] Obtain the target rejection factors corresponding to several risk material categories of the business application materials and aggregate them to obtain the target risk data;

[0112] Step S300: Obtain the historical application process records of the enterprise, and in combination with the target risk data, trace the business application process in the enterprise to identify the root causes affecting the enterprise's business application and obtain the target abnormal data;

[0113] Among them, Step S300 includes:

[0114] Step S301: Obtain the historical application process records of the business application materials in the enterprise, and from the application process records, obtain the process departments related to each material category in the business application materials;

[0115] Step S302: Trace the business application process in the enterprise to identify the root causes affecting the enterprise's business application. The specific tracing process is as follows:

[0116] Obtain the target risk data of each business application material of the enterprise in the current period, and obtain the risk material categories in each business application material;

[0117] Step S303: When a certain process department is the process department related to several risk material categories in a certain business application material, obtain the total number of several risk material categories and record it as the characteristic abnormal value of a certain process department in a certain business application material;

[0118] Obtain the abnormal process departments of each target risk material category in each business application material, and calculate the application impact value of each process department responsible for business application in the enterprise. Among them, the application impact value Uk of the k-th process department in the enterprise k :

[0119]

[0120] Among them, s is the total number of all business application materials; P k (z,sum) is the characteristic abnormal value of the k-th process department in the z-th business application material among all business application materials;

[0121] Step S304: When the application impact value Uk kIf it is greater than the preset threshold for the impact of application, it is determined that the k-th process department is the root cause affecting the enterprise's business application, and the k-th process department is recorded as an abnormal process department. Each abnormal process department of the enterprise is obtained and aggregated to obtain the target abnormal data of the enterprise;

[0122] Step S400: Obtain the target abnormal data, generate the business application suggestion data of the enterprise, push it to the enterprise, and supervise the application process of the enterprise to assist the enterprise in applying for business to the approval agency;

[0123] Among them, step S400 includes:

[0124] Step S401: Obtain the target abnormal data of the enterprise, obtain each abnormal process department from the target abnormal data, and obtain the target risk data of each business application material of the enterprise in the current cycle;

[0125] Step S402: Obtain the risk target rejection factors corresponding to the risk material categories from the target risk data, obtain several risk target rejection factors corresponding to the risk material categories related to a certain abnormal process department, and based on the work log of a certain abnormal process department, obtain the solutions corresponding to several risk target rejection factors from the application assistance platform to obtain the application suggestion data of a certain process department in the enterprise, and push it to the person in charge of the department of a certain process department;

[0126] Supervise the enterprise in the process of preparing business application materials and assist the enterprise in applying for business to the approval agency. The specific process is as follows:

[0127] When none of the material categories in the business application materials of the enterprise are marked as risk material categories again, it is determined that the business application materials of the enterprise are allowed to be submitted to the approval agency, otherwise the business application materials are continued to be modified until none of the material categories in the business application materials are marked as risk material categories;

[0128] In order to better implement the above method, a multi-process data integration traceability supervision system based on cloud services is also proposed. The system includes a rejection factor evaluation module, a rejection risk evaluation module, a cause traceability module, and an intelligent supervision module;

[0129] The rejection factor evaluation module is used to evaluate the impact degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise to obtain the target rejection data;

[0130] The rejection risk evaluation module is used to evaluate the business rejection risk of the business application materials in the approval process of the approval agency to obtain the target risk data;

[0131] A cause tracing module for tracing the business application process in an enterprise, identifying the root causes affecting the enterprise's business application, and obtaining target abnormal data;

[0132] An intelligent supervision module for pushing the generated business application suggestion data of the enterprise to the enterprise, supervising the application process of the enterprise, and assisting the enterprise to conduct business applications to the approval agency;

[0133] Among them, the rejection factor evaluation module includes a rejection impact value unit and a rejection factor evaluation unit;

[0134] The rejection impact value unit is used to calculate the rejection factors in the approval process of the approval agency and the rejection impact value of the enterprise's business application;

[0135] The rejection factor evaluation unit is used to evaluate the impact degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise according to the rejection impact value, and obtain the target rejection data;

[0136] Among them, the rejection risk assessment module includes a data acquisition unit and a rejection risk assessment unit;

[0137] The data acquisition unit is used to obtain the business application materials uploaded by the enterprise in the application assistance platform and obtain the historical application texts corresponding to each material category from the historical application rejection records of the approval agency;

[0138] The rejection risk assessment unit is used to assess the business rejection risk of the business application materials in the approval process of the approval agency and obtain the target risk data;

[0139] Among them, the cause tracing module includes an application impact value unit and a cause tracing unit;

[0140] The application impact value unit is used to calculate the application impact value of each process department responsible for the enterprise's business application;

[0141] The cause tracing unit is used to trace the business application process in the enterprise according to the application impact value, identify the root causes affecting the enterprise's business application, and obtain the target abnormal data of the enterprise;

[0142] Among them, the intelligent supervision module includes an intelligent supervision unit;

[0143] The intelligent supervision unit is used to obtain the target abnormal data of the enterprise, obtain the solutions corresponding to several risk target rejection factors from the application assistance platform, obtain the application suggestion data of a certain process department in the enterprise, and push it to the person in charge of the department of a certain process department, and conduct intelligent supervision on the enterprise in the process of preparing business application materials.

[0144] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims concerned.

Claims

1. A multi-process data integration traceability and supervision method based on cloud services, characterized in that The method includes: Step S100: Obtain the historical application rejection records in the approval agency for the enterprise's business application, obtain the rejection factors of the characteristic rejection data in the enterprise's application assistance platform, evaluate the influence degree of the rejection factors on the business applied by the enterprise during the approval process of the approval agency, and obtain the target rejection data; Step S200: Obtain the business application materials uploaded by the enterprise in the application assistance platform, obtain the target rejection data, evaluate the business rejection risk of the business application materials during the approval process of the approval agency, and obtain the target risk data; Step S300: Obtain the historical application process records of the enterprise, and in combination with the target risk data, trace the business application process in the enterprise, identify the root causes affecting the enterprise's business application, and obtain the target exception data; Step S400: Obtain the target exception data, generate the business application suggestion data for the enterprise, push it to the enterprise, and supervise the application process of the enterprise to assist the enterprise in applying for the business to the approval agency.

2. The multi-process data integration traceability supervision method based on cloud service according to claim 1, wherein, The step S100 includes: Step S101: Obtain the approval agency that approves the business applied by the enterprise, obtain each historical application rejection record in the approval agency from the pre-constructed application assistance platform, and obtain the historical rejection text from the historical application rejection records; Step S102: Obtain the characteristic rejection data in the application assistance platform, where the characteristic rejection data includes the text content corresponding to each preset rejection factor in the application assistance platform; Perform text preprocessing on the historical rejection text, and based on a preset sentence splitting model, split the historical rejection text into sentences, obtain each sentence in the historical rejection text, and collect them to obtain the sentence set in the historical rejection text; Step S103: Use the pre-constructed sentence vector model in the application assistance platform to obtain the characteristic vectors corresponding to each sentence in the sentence set. Based on the text content corresponding to each rejection factor in the application assistance platform, and in combination with the sentence splitting model and the sentence vector model, obtain the sentence vector set of each rejection factor; Obtain the feature vector of a certain sentence in the historical rejection text, and obtain the maximum value R of the cosine similarity between the certain sentence and each element in the sentence vector set of each rejection factor max , and obtain the maximum value R max At this time, a certain rejection factor corresponding to the certain sentence; Step S104: When the maximum value R of the cosine similarity max is greater than a preset similarity threshold, determine that the certain sentence is the characteristic sentence of the certain rejection factor; Step S105: Obtain the sum A of the total number of characteristic sentences of each of the rejection factors in the historical rejection text sum , calculate the characteristic influence value B' of a certain rejection factor in the historical application rejection record = A' sum / A sum , where A' sum is the total number of characteristic sentences in the historical rejection text of a certain rejection factor in the historical application rejection record; When the characteristic influence value B' is greater than the preset characteristic influence threshold, record the historical application rejection record as the marked historical application rejection record of a certain rejection factor; Calculate the rejection influence value C' of a certain rejection factor on the enterprise's application business during the approval process of the approval agency: where j is the total number of all the historical application rejection records; B′ i is the characteristic influence value of the i-th historical application rejection record of a certain rejection factor in the approval authority; Step S106: When the rejection influence value C' is greater than the preset rejection influence threshold, determine that a certain rejection factor has an impact on the rejection of the business applied by the enterprise during the approval process of the approval agency, and record the certain rejection factor as the target rejection factor; Obtain each target rejection factor in the review agency, obtain the marked historical application rejection records of each target rejection factor, and collect them to obtain the target rejection data.

3. The multi-process data integration traceability supervision method based on cloud service according to claim 2, characterized in that The step S200 includes: Step S201: Obtain the business application materials uploaded by the enterprise in the application assistance platform, and obtain the application texts corresponding to each material category from the business application materials; Step S202: Obtain the target rejection data of the approval agency, obtain each target rejection factor from the target rejection data, obtain the marked historical application rejection records corresponding to each target rejection factor, and obtain the historical application texts corresponding to each material category from the marked historical application rejection records; Step S203: Evaluate the business rejection risk of the business application materials during the approval process of the approval agency. The specific evaluation process is as follows: Obtain the application text D corresponding to a certain material category in the business application materials, and obtain the historical application text F of the certain material category in a certain marked application rejection record corresponding to a certain target rejection factor; Divide the application text D and the historical application text F into text blocks respectively, and use a text conversion tool to convert a certain text block in the application document D and another historical text block in the historical application document F into several strings and gather them to obtain a file string set D' and a historical file string set F'; Step S205: When the business application materials contain risk material categories, determine that there is a business rejection risk in the business application materials during the approval process of the approval agency; Obtain the risk target rejection factors corresponding to several risk material categories of the business application materials and gather them to obtain target risk data. Obtain the last element H[m][n] in the lower right corner of the two-dimensional array H, where n represents the total number of strings in the file string set D′, and m represents the total number of strings in the historical file string set F′, and calculate the text block similarity value R′ between a certain text block and another historical text block (d，f) : The step S300 includes: Obtain the mean of the feature text similarity values between several text blocks in the bid application text D and the historical bid application document F, and denote it as the text similarity value Q between the bid application text D and the historical bid application document F (d,f) ; When the text similarity value Q (d,f) is greater than the preset text similarity threshold, it is determined that there is a risk that the business application materials are rejected due to the rejection factor of a certain project target. Record the certain material category as the risk material category, obtain the rejection factor of the certain project target, and record it as the risk target rejection factor of the risk material category; Step S301: Obtain the historical application process records of the business application materials in the enterprise, and obtain the process departments related to each material category in the business application materials from the application process records; Step S302: Trace the source of the business application process in the enterprise to identify the root cause affecting the enterprise's business application. The specific tracing process is as follows:

4. The multi-process data integration traceability and supervision method based on cloud service according to claim 3, characterized in that ​ ​ ​ Obtain the target risk data of each business application material of the enterprise in the current period, and obtain the risk material categories in each business application material; Step S303: When a certain process department is the process department related to several risk material categories in a certain business application material, obtain the total number of items of the several risk material categories, and record it as the characteristic outlier value of the certain process department in the certain business application material; Obtain the abnormal process departments of each target risk material category in the application materials for each business, and calculate the application impact value of each process department responsible for business applications of the enterprise, where the application impact value U of the k-th process department in the enterprise k : where s is the total number of the application materials for each service; P k (z,sum) is the outlier of the k-th process department in the z-th application material among the application materials for each service. Step S304: When the application impact value U k is greater than a preset application impact threshold, it is determined that the k-th process department is the root cause affecting the enterprise's business application, and the k-th process department is recorded as an abnormal process department. Each abnormal process department of the enterprise is obtained and aggregated to obtain the target abnormal data of the enterprise.

5. A multi-process data integration traceability supervision method based on cloud services according to claim 4, characterized in that, The said step S400 includes: Step S401: Obtain the target abnormal data of the enterprise, obtain each abnormal process department from the target abnormal data, and obtain the target risk data of each business application material of the enterprise in the current period; Step S402: Obtain the risk target rejection factors corresponding to the risk material categories from the target risk data, obtain several risk target rejection factors corresponding to the risk material categories related to a certain abnormal process department, and based on the work log of the certain abnormal process department, obtain the solutions corresponding to the several risk target rejection factors from the application assistance platform, obtain the application suggestion data of the certain process department in the enterprise, and push it to the person in charge of the certain process department; Supervise the enterprise in the process of preparing business application materials, and assist the enterprise in applying for business to the approval agency. The specific process is as follows: When none of the material categories in the business application materials of the enterprise is marked as a risk material category again, it is determined that the business application materials of the enterprise are allowed to be submitted to the approval agency; otherwise, continue to modify the business application materials until none of the material categories in the business application materials is marked as a risk material category.

6. A multi-process data integration traceability supervision system based on cloud services, which is used to execute a multi-process data integration traceability supervision method based on cloud services described in any one of claims 1-5, and is characterized in that, The said system includes a rejection factor evaluation module, a rejection risk evaluation module, a cause tracing module, and an intelligent supervision module; The rejection factor evaluation module is used to evaluate the influence degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise, and obtain the target rejection data; The rejection risk evaluation module is used to evaluate the business rejection risk of the business application materials in the approval process of the approval agency, and obtain the target risk data; The cause tracing module is used to trace the business application process in the enterprise, identify the root cause affecting the enterprise's business application, and obtain the target abnormal data; The intelligent supervision module is used to push the generated business application suggestion data of the enterprise to the enterprise, supervise the enterprise's application process, and assist the enterprise in applying for business to the approval agency.

7. A multi-process data integration traceability and supervision system based on cloud services according to claim 6, characterized in that, The rejection factor evaluation module includes a rejection influence value unit and a rejection factor evaluation unit; The rejection influence value unit is used to calculate the rejection influence value of each rejection factor in the approval process of the approval agency on the business applied by the enterprise; The rejection factor evaluation unit is used to evaluate the influence degree of the rejection factors in the approval process of the approval agency on the business applied by the enterprise according to the rejection influence value, and obtain the target rejection data.

8. The multi-process data integration traceability and supervision system based on cloud service according to claim 6, characterized in that The rejection risk assessment module includes a data acquisition unit and a rejection risk assessment unit; The data acquisition unit is used to acquire the business application materials uploaded by the enterprise in the application assistance platform, and acquire the historical application texts corresponding to each material category from the historical application rejection records of the approval agency; The rejection risk assessment unit is used to assess the business rejection risk of the business application materials during the approval process of the approval agency to obtain target risk data.

9. A multi-process data integration traceability and supervision system based on cloud services according to claim 6, characterized in that, The cause tracing module includes an application impact value unit and a cause tracing unit; The application impact value unit is used to calculate the application impact values of each process department responsible for business application of the enterprise; The cause tracing unit is used to trace the business application process in the enterprise according to the application impact value, identify the root cause affecting the enterprise's business application, and obtain the target abnormal data of the enterprise.

10. A multi-process data integration traceability supervision system based on cloud services according to claim 6, characterized in that, The intelligent supervision module includes an intelligent supervision unit; The intelligent supervision unit is used to acquire the target abnormal data of the enterprise, obtain the solutions corresponding to the several risk target rejection factors from the application assistance platform, obtain the application suggestion data of a certain process department in the enterprise, and push it to the person in charge of the department of a certain process department, and conduct intelligent supervision on the enterprise during the preparation of business application materials.

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