Visualization-based acquisition payment business process arrangement method and system

Abstract

The invention relates to the technical field of financial science and technology, and discloses a visualization-based acquisition payment business process arrangement method and system, and the method comprises the steps: obtaining a business unit set marked with business functions, obtaining an initial business function set based on the business unit set and an initial sorting unit, obtaining a scene recognition text, and carrying out the scene recognition text; extracting a scene text sequence from the scene recognition text, acquiring a matched service unit sequence by using the scene text sequence and the initial service function set, driving the matched service unit sequence, if the matched service unit sequence is successfully driven, generating a first matching report by using the matched service unit sequence, otherwise, generating a second matching report by using the matched service unit sequence. And obtaining a plurality of evaluation service unit sequences by using the scene text sequence and the initial service function set, determining a target service unit sequence according to the plurality of evaluation service unit sequences, and generating a second matching report by using the target service unit sequence. According to the invention, the intelligent degree of payment process arrangement can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fintech, and in particular to a method and system for choreographing the acquiring payment business process based on visualization. Background Art

[0002] With the penetration of mobile payment in multiple scenarios, various differentiated acquiring payment requirements have emerged. However, the traditional acquiring payment business architecture cannot meet the elastic adaptation requirements of scenario-based services. Correspondingly, how to intelligently choreograph the payment process has become an urgent problem to be solved.

[0003] Currently, traditional payment process choreography mostly adopts the method of manual coding to achieve the choreography of the payment process.

[0004] Although the above method can achieve the choreography of the payment process, when choreographing the payment process, there are problems of low choreography efficiency and poor operation and maintenance capabilities. Therefore, accurately and intelligently realizing the choreography of the payment process has become an urgent problem to be solved. Summary of the Invention

[0005] The present invention provides a method for choreographing the acquiring payment business process based on visualization and a computer-readable storage medium, and its main purpose is to improve the intelligent degree of payment process choreography.

[0006] To achieve the above object, a method for choreographing the acquiring payment business process based on visualization provided by the present invention includes: Receiving a process choreography instruction, and confirming a process choreography system based on the process choreography instruction, wherein the process choreography system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit; Obtaining a set of business units marked with business functions, wherein the set of business units includes multiple business units, and each business unit in the multiple business units is marked with a business function. Based on the set of business units and the initial sorting unit, obtaining an initial set of business functions, wherein the initial set of business functions includes multiple initial business function sequences, and the initial business function sequences correspond to the business functions one by one; Confirming to receive a scenario recognition instruction from the scenario recognition unit, parsing the scenario recognition instruction to obtain a scenario recognition text, and extracting a scenario text sequence from the scenario recognition text, wherein the scenario text sequence includes multiple scenario keywords; Using the scenario text sequence and the initial set of business functions to obtain a matching business unit sequence, driving the matching business unit sequence, and if the matching business unit sequence is successfully driven, generating a first matching report using the matching business unit sequence; Otherwise, obtain multiple evaluated business unit sequences using the scenario text sequence and the initial business function set, confirm the target business unit sequence based on the multiple evaluated business unit sequences, and generate a second matching report using the target business unit sequence; Use the result feedback unit to send the first matching report or the second matching report to the initiator of the process choreography instruction, so as to realize the process choreography of the payment service.

[0007] Optionally, the obtaining of the initial business function set based on the business unit set and the initial sorting unit includes: Confirm the receipt of the initial sorting instruction from the initial sorting unit, and parse the initial sorting instruction to obtain a process text set, where the process text set includes multiple process texts; Perform the following operations on each process text in the process text set: Use a pre-built language processing model, a pre-built corpus, and the process text to obtain a process keyword sequence, where the process keyword sequence includes multiple process keywords; Summarize the process keyword sequences to obtain multiple process keyword sequences, and perform a merging operation on the multiple process keyword sequences using the corpus to obtain multiple initial function texts; Use the multiple initial function texts and the business unit set to obtain the initial business function set.

[0008] Optionally, the obtaining of the initial business function set using the multiple initial function texts and the business unit set includes: Perform the following operations on each initial function text in the multiple initial function texts: Count the number of times the initial function text appears in the multiple process keyword sequences to obtain a statistical quantity, summarize the statistical quantities to obtain a statistical quantity set, and calculate a text statistical ratio set using the statistical quantity set. The calculation formula is as follows: where represents the th text statistical ratio in the text statistical ratio set, represents the th statistical quantity in the statistical quantity set, represents the total number of statistical quantities in the statistical quantity set, represents the th statistical quantity in the statistical quantity set; Use a preset statistical ratio threshold to extract a target statistical ratio set from the text statistical ratio set, where the target statistical ratio set includes multiple target statistical ratios, and the target statistical ratio is greater than or equal to the statistical ratio threshold. Perform the following operations on each target statistical ratio in the multiple target statistical ratios: Update the business functions corresponding to the business units in the business unit set according to the initial function text corresponding to the target statistical ratio to obtain an updated business unit set, where the updated business unit set includes multiple business units marked with updated business functions; Summarize the business units in the updated business unit set according to the updated business functions respectively to obtain multiple classified business unit sets, and use the multiple classified business unit sets to obtain an initial business function set.

[0009] Optionally, the obtaining the initial business function set by using the multiple classified business unit sets includes: Perform the following operations on each classified business unit in the multiple classified business unit sets: Obtain the average response time of the classified business unit, calculate the unit evaluation value based on the average response time and a pre-constructed unit evaluation relational expression, summarize the unit evaluation values to obtain a unit evaluation value set, sort the unit evaluation values in the unit evaluation value set in descending order to obtain a unit evaluation value sequence; Map the initial business function sequence according to the rank of the classified business unit in the unit evaluation value sequence.

[0010] Optionally, the unit evaluation relational expression is as follows: Wherein, represents the unit evaluation value, are all preset coefficients, represents the throughput of the classified business unit, represents the expected throughput of the classified business unit, represents the maximum response time of the classified business unit, represents the average response time of the classified business unit, represents the successful request rate of the classified business unit, represents the average fault diagnosis time of the classified business unit, represents the extended score of the classified business unit.

[0011] Optionally, the obtaining the matching business unit sequence by using the scenario text sequence and the initial business function set includes: Update the scenario keywords in the scenario text sequence by using multiple initial function texts to obtain an updated scenario keyword sequence; Use the updated scenario keywords in the updated scenario keyword sequence to retrieve a retrieved business function set from the initial business function set, where the retrieved business function set includes multiple retrieved business function sequences; Perform the following operations on each retrieved business function sequence in the multiple retrieved business function sequences: Extract the first retrieval service unit from the retrieval service function sequence, summarize the first retrieval service unit to obtain a retrieval service unit set, and obtain a matching service unit sequence according to the updated scenario keyword sequence and the retrieval service unit set.

[0012] Optionally, the obtaining of multiple evaluation service unit sequences by using the scenario text sequence and the initial service function set includes: Perform the following operations on each retrieval service function sequence in the service function set: Use a preset extraction value to extract a matching service function sequence from the retrieval service function sequence, summarize the matching service function sequences to obtain multiple matching service function sequences; Count the quantity of each scenario text in the scenario text sequence to obtain a matching quantity group, where the matching quantity group is as follows: Among them, represents the matching quantity group, respectively represent the first matching quantity in the matching quantity group and the second matching quantity in the matching quantity group, represents that there are matching quantities in the matching quantity group; Perform the following operations on the matching quantities in the matching quantity group: In a combined form, use the matching quantity group and the matching service function sequence corresponding to the matching quantity to obtain a matching service function group set, summarize the matching service function group set to obtain multiple matching service function group sets, and in a permutation form, use the multiple matching service function group sets and the scenario text sequence to obtain multiple evaluation service unit sequences.

[0013] Optionally, the confirmation of the target service unit sequence according to multiple evaluation service unit sequences includes: Perform the following operations on each evaluation service unit sequence in the multiple evaluation service unit sequences: Obtain an evaluation factor set of the evaluation service unit sequence, and calculate an evaluation reference value by using the evaluation factor set. The calculation formula is as follows: Among them, represents the evaluation reference value, represents the preset rd coefficient, represents the th evaluation factor in the evaluation factor set, represents that there are evaluation factors in the evaluation factor set; Summarize the above evaluation reference values to obtain an evaluation reference value set, and use the evaluation reference value set to obtain a target business unit sequence.

[0014] Optionally, the step of using the evaluation reference value set to obtain a target business unit sequence includes: Sort the evaluation reference values in the evaluation reference value set in descending order to obtain an evaluation reference value sequence, and use a preset evaluation extraction value to confirm an extraction reference value sequence in the evaluation reference value sequence; Obtain multiple reference comparison sequences based on the extraction reference value sequence, where the reference comparison sequences correspond to the evaluation factors one by one, and the order of the reference comparison values in the reference comparison sequence is the same as the order of the evaluation reference values in the extraction reference value sequence; If the first reference comparison value in each of the multiple reference comparison sequences is the maximum value, then use the evaluation business unit sequence corresponding to the first extraction reference value in the extraction reference value sequence as the target business unit sequence.

[0015] To achieve the above object, the present invention also provides a visualization-based acquiring payment service process choreography system, including: A business unit acquisition module, configured to receive a process choreography instruction, and confirm a process choreography system based on the process choreography instruction, where the process choreography system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit; Obtain a business unit set marked with business functions, where the business unit set includes multiple business units, and each business unit in the multiple business units is marked with a business function, and obtain an initial business function set based on the business unit set and the initial sorting unit, where the initial business function set includes multiple initial business function sequences, and the initial business function sequences correspond to the business functions one by one; A business scenario recognition module, configured to confirm and receive a scenario recognition instruction from the scenario recognition unit, parse the scenario recognition instruction to obtain a scenario recognition text, and extract a scenario text sequence from the scenario recognition text, where the scenario text sequence includes multiple scenario keywords; A business unit choreography module, configured to obtain a matching business unit sequence by using the scenario text sequence and the initial business function set, drive the matching business unit sequence, and if the matching business unit sequence is successfully driven, generate a first matching report by using the matching business unit sequence; Otherwise, obtain multiple evaluation business unit sequences by using the scenario text sequence and the initial business function set, confirm a target business unit sequence according to the multiple evaluation business unit sequences, and generate a second matching report by using the target business unit sequence; An arrangement result feedback module, configured to use the result feedback unit to send the first matching report or the second matching report to the initiating end of the process arrangement instruction, so as to implement the process arrangement of the payment service.

[0016] To solve the above problems, the present invention further provides an electronic device, which includes: A memory that stores at least one instruction; and a processor that executes the instructions stored in the memory to implement the above-mentioned visualization-based acquiring payment service process arrangement method.

[0017] To solve the above problems, the present invention further provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned visualization-based acquiring payment service process arrangement method.

[0018] To solve the problems described in the background art, the present invention obtains a set of service units marked with service functions. Among them, the set of service units includes multiple service units, and each service unit in the multiple service units is marked with a service function. Based on the set of service units and the initial sorting unit, an initial service function set is obtained. Among them, the initial service function set includes multiple initial service function sequences, and the initial service function sequences correspond one-to-one with the service functions. It can be seen that the present invention marks the service units in combination with the text used in the actual situation, so as to facilitate the division and classification of the service units, and screen the service units, and screen out the frequently used service units, and evaluate the frequently used service units, so as to clarify the usage order of different service units under the same function in the theoretical situation, laying a foundation for the subsequent orchestration of payment services. Confirm the receipt of the scene recognition instruction from the scene recognition unit, parse the scene recognition instruction to obtain the scene recognition text, and extract the scene text sequence from the scene recognition text. Among them, the scene text sequence includes multiple scene keywords. It can be seen that the present invention combines the specific usage scenario, and through the analysis of the usage scenario, obtains the representation text for orchestrating different service units. Use the scene text sequence and the initial service function set to obtain a matching service unit sequence, and drive the matching service unit sequence. If the matching service unit sequence is successfully driven, use the matching service unit sequence to generate a first matching report. Otherwise, use the scene text sequence and the initial service function set to obtain multiple evaluated service unit sequences, confirm the target service unit sequence according to the multiple evaluated service unit sequences, and use the target service unit sequence to generate a second matching report. It can be seen that the present invention considers that in the theoretical situation, the orchestration of service units may not meet the compatibility requirements. Therefore, it screens the service units with different functions again, obtains multiple evaluated service unit sequences in a combined form, and evaluates the evaluated service unit sequences. After confirming that the optimal evaluated service unit sequence is optimal in each dimension, the target service unit sequence is obtained, and the service units used are clarified in the form of generating a report, improving the intelligence level of the present invention. Therefore, the present invention can improve the intelligence level of the payment process orchestration. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 FIG. is a schematic flowchart of a method for orchestrating the payment business process based on visualization provided by an embodiment of the present invention; Figure 2 FIG. is a functional module diagram of a system for orchestrating the payment business process based on visualization provided by an embodiment of the present invention; The implementation, functional features and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the drawings. DETAILED DESCRIPTION OF THE INVENTION

[0020] It should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0021] An embodiment of the present application provides a method for choreographing the acquiring payment business process based on visualization. The execution subject of the method for choreographing the acquiring payment business process based on visualization includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for choreographing the acquiring payment business process based on visualization can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0022] Refer to Figure 1 As shown, it is a flowchart of a method for choreographing the acquiring payment business process based on visualization provided by an embodiment of the present invention. In this embodiment, the method for choreographing the acquiring payment business process based on visualization includes: S1. Receive a process choreography instruction, and confirm a process choreography system based on the process choreography instruction. Among them, the process choreography system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit.

[0023] It should be explained that the process choreography instruction is an instruction issued by a software tester or a software developer, and is used to implement the testing of software in different application scenarios. In the embodiment of the present invention, the software refers to software composed of units with different business functions. The process choreography system refers to a small program or APP that can match different software according to different application scenarios, and the process choreography system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit. For the specific application of the unit, please refer to the subsequent embodiments.

[0024] Exemplarily, in order to develop a software applied to a specific scenario, a software developer issues the process choreography instruction and confirms the process choreography system.

[0025] S2. Obtain a set of business units marked with business functions. Among them, the set of business units includes multiple business units, and each business unit in the multiple business units is marked with a business function. Based on the set of business units and the initial sorting unit, obtain an initial set of business functions. Among them, the initial set of business functions includes multiple initial business function sequences, and the initial business function sequences correspond to the business functions one by one.

[0026] It should be explained that a business unit refers to a unit or node that can achieve specific functions. Business functions refer to the functions that a business unit can achieve. For example, payment, feedback. For example, by means of coding, a code that can generate a random number between 1 and 10 is edited, and this code is a business unit marked with random number generation.

[0027] It can be understood that obtaining the initial business function set based on the business unit set and the initial sorting unit includes: Confirm the receipt of the initial sorting instruction from the initial sorting unit, parse the initial sorting instruction to obtain a set of process texts, where the set of process texts includes multiple process texts; Perform the following operations on each process text in the set of process texts: Use a pre-built language processing model, a pre-built corpus, and the process text to obtain a sequence of process keywords, where the sequence of process keywords includes multiple process keywords; Summarize the sequence of process keywords to obtain multiple sequences of process keywords, and perform a merging operation on the multiple sequences of process keywords using the corpus to obtain multiple initial function texts; Use the multiple initial function texts and the business unit set to obtain the initial business function set.

[0028] It should be understood that the process text refers to the text used to describe the implementation process of a certain business when implementing the business. The set of process texts can be obtained by means of artificial setting. The language processing model refers to a model that can screen or eliminate texts. Optionally, a natural language processing model is used as the language processing model, and the same effect can be achieved by using other technologies, which will not be elaborated here. The corpus refers to a database storing texts used to describe different business functions. Optionally, the corpus is obtained by means of artificial formulation, and the same effect can be achieved by using other technologies, which will not be elaborated here. The sequence of process keywords refers to the sequence of texts extracted according to the process text for realizing different functions. Process keywords are keywords used to describe different business functions.

[0029] Exemplarily, the process text is: When accumulating points, it is necessary to make a payment first. After converting the amount paid into corresponding points, the points are accumulated on the original points. Using the language processing model and the corpus, three process keywords can be extracted from the process text: payment, point conversion, and point accumulation. After sorting the process keywords in the order of their appearance in the process text from first to last, a sequence of process keywords is obtained, where the sequence of process keywords is: payment, point conversion, point accumulation.

[0030] Further, the keywords used to describe functions in different process texts may be different. Therefore, multiple process keyword sequences can be obtained by processing the process texts in the process text set. The operation of merging multiple process keyword sequences using a corpus means updating the process keywords in the process keyword sequences to words with the same meaning. For example, the accumulation of points can be expressed as the statistics of points, the summation of points, etc. Here, the operations of accumulation, statistics, and summation are merged and can be merged into: accumulation, that is, both statistics and summation can be expressed by accumulation. Updating multiple process keyword sequences using multiple initial function texts means updating process keywords with the same meaning to the same process keyword.

[0031] It should be explained that the obtaining of the initial service function set by using multiple initial function texts and the service unit set includes: Perform the following operations on each of the multiple initial function texts: Count the number of times the initial function text appears in the multiple process keyword sequences to obtain the count quantity, summarize the count quantities to obtain the count quantity set, and calculate the text count ratio set using the count quantity set. The calculation formula is as follows: Where, represents the th text count ratio in the text count ratio set, represents the th count quantity in the count quantity set, represents the total number of count quantities in the count quantity set, represents the th count quantity in the count quantity set; Use a preset statistical ratio threshold to extract the target statistical ratio set from the text count ratio set. Among them, the target statistical ratio set includes multiple target statistical ratios, and the target statistical ratio is greater than or equal to the statistical ratio threshold. Perform the following operations on each of the multiple target statistical ratios: Update the service functions corresponding to the service units in the service unit set according to the initial function text corresponding to the target statistical ratio to obtain the updated service unit set. Among them, the updated service unit set includes multiple service units marked with updated service functions; Summarize the service units in the updated service unit set according to the updated service functions respectively to obtain multiple classified service unit sets, and use the multiple classified service unit sets to obtain the initial service function set.

[0032] It is understandable that updating the business functions corresponding to the business units in the business unit set according to the initial function text corresponding to the target statistical ratio means using a language processing model and the initial function text to identify, among multiple business functions, the business functions with the same meaning as the initial function text, and updating this business function to the initial function text. Here, the initial function text used for updating is the updated business function.

[0033] It should be explained that obtaining the initial business function set by using the multiple classified business unit sets includes: Performing the following operations on each classified business unit in the multiple classified business unit sets: Obtaining the average response time of the classified business unit, calculating the unit evaluation value based on the average response time and a pre-constructed unit evaluation relation formula, summarizing the unit evaluation values to obtain a unit evaluation value set, sorting the unit evaluation values in the unit evaluation value set from largest to smallest to obtain a unit evaluation value sequence; Mapping the initial business function sequence according to the position order of the classified business unit in the unit evaluation value sequence.

[0034] It is understandable that the average response time refers to the average time required for the business classification unit to process a request. Generally, there is a one-to-one correspondence between the classified business unit and the unit evaluation value. Therefore, the initial business function sequence can be obtained according to the position order of the unit evaluation value corresponding to the classified business unit in the unit evaluation value sequence. For example, there are currently 3 classified business units, and the unit evaluation values corresponding to the 3 classified business units are 3, 5, and 2 respectively, that is, the unit evaluation value corresponding to the first classified business unit is 3, the unit evaluation value corresponding to the second classified business unit is 5, and the unit evaluation value corresponding to the third classified business unit is 2. The unit evaluation value sequence obtained by using the unit evaluation values corresponding to the classified business units is 5, 3, 2, and the initial business function sequence obtained according to the unit evaluation value sequence is: the second classified business unit, the first classified business unit, and the third classified business unit.

[0035] Furthermore, the unit evaluation relation formula is as follows: Wherein, represents the unit evaluation value, are all preset coefficients, represents the throughput of the classified business unit, represents the expected throughput of the classified business unit, represents the maximum response time of the classified business unit, represents the average response time of the classified business unit, represents the successful request rate of the classified business unit, Represents the average fault diagnosis time of the classification business unit, Represents the extended score of the classification business unit.

[0036] It should be explained that the expected throughput refers to the throughput of the classification business unit under theoretical conditions, the maximum response time refers to the maximum preset time allowed for the classification business unit to respond, the successful request rate refers to the probability that the classification business unit successfully processes requests, and the average fault diagnosis time refers to the average time required to diagnose the classification business unit when a fault occurs in the classification business unit. The extended score is a score used to evaluate whether the classification business unit supports capacity expansion. Optionally, the indicated extended score is obtained in the form of manual setting. For example, when the classification business unit cannot be expanded, the extended score is set to 0; when the classification business unit only supports manual expansion, the extended score is set to 0.5; when the classification business unit supports dynamic expansion, the extended score is set to 1. Optionally, the analytic hierarchy process is used to evaluate the classification business unit to obtain the coefficients in the unit evaluation relationship. The same effect can be achieved by using other technologies and will not be elaborated here.

[0037] S3. Confirm the receipt of the scene recognition instruction from the scene recognition unit, parse the scene recognition instruction to obtain the scene recognition text, and extract the scene text sequence from the scene recognition text, where the scene text sequence includes multiple scene keywords.

[0038] It should be explained that the scene recognition text is the text used to describe the software functions to be generated. Optionally, the scene recognition text is input by software developers in the process orchestration system. The method of extracting the scene text sequence from the scene recognition text is the same as the method of obtaining process keywords using process text and will not be elaborated here.

[0039] S4. Use the scene text sequence and the initial business function set to obtain the matching business unit sequence, drive the matching business unit sequence, and if the matching business unit sequence is successfully driven, generate the first matching report using the matching business unit sequence.

[0040] It can be understood that the obtaining of the matching business unit sequence using the scene text sequence and the initial business function set includes: Updating the scene keywords in the scene text sequence using multiple initial function texts to obtain the updated scene keyword sequence; Using the updated scene keywords in the updated scene keyword sequence to retrieve the retrieved business function set from the initial business function set, where the retrieved business function set includes multiple retrieved business function sequences; Perform the following operations on each retrieved business function sequence in the multiple retrieved business function sequences: Extract the first retrieval service unit in the retrieval service function sequence, summarize the first retrieval service unit to obtain a retrieval service unit set, and obtain a matching service unit sequence according to the updated scenario keyword sequence and the retrieval service unit set.

[0041] Further, the method of updating the scenario keywords in the scenario text sequence using multiple initial function texts is the same as the method of updating the service functions corresponding to the service units in the service unit set according to the initial function text corresponding to the target statistical ratio, which will not be elaborated here. The purpose of obtaining the updated scenario keyword sequence is to unify the names of the service functions corresponding to the service units. The initial function text corresponding to the retrieval service function sequence is the same as the updated scenario keyword, that is, using the updated scenario keywords in the updated scenario keyword sequence to retrieve the retrieval service function set in the initial service function set means retrieving the initial service function sequence that is the same as the updated scenario keyword in the initial service function set. The method of obtaining the matching service unit sequence according to the updated scenario keyword sequence and the retrieval service unit set is the same as the method of mapping the initial service function sequence based on the rank of the classification service unit in the unit evaluation value sequence, which will not be elaborated here. Generally speaking, the obtained matching service unit sequence aggregates the best service units in different service functions. Therefore, it can be considered that the obtained matching service unit sequence is the unit used to execute the scenario described in the scenario recognition text under ideal circumstances.

[0042] It should be explained that the matching service units in the matching service unit sequence obtained using the best service units may not be compatible during execution. Therefore, there may be a situation where the matching service unit sequence cannot be successfully executed. When the matching service unit sequence can be successfully executed, extract the ranks of the matching service units in the matching service unit sequence in different initial service function sequences, and mark the ranks of the matching service units in the corresponding initial service function sequences in the matching service unit sequence to obtain a first matching report.

[0043] S5. Otherwise, obtain multiple evaluation service unit sequences using the scenario text sequence and the initial service function set, confirm a target service unit sequence based on the multiple evaluation service unit sequences, and generate a second matching report using the target service unit sequence.

[0044] It should be explained that the obtaining of multiple evaluation service unit sequences using the scenario text sequence and the initial service function set includes: Perform the following operations on each retrieval service function sequence in the service function set: Use a preset extraction value to extract a matching service function sequence in the retrieval service function sequence, and summarize the matching service function sequences to obtain multiple matching service function sequences; Count the number of each scenario text in the scenario text sequence to obtain a matching quantity group, where the matching quantity group is as follows: Among them, represents the matching quantity group, respectively represent the first matching quantity in the matching quantity group and the second matching quantity in the matching quantity group, represents that there are matching quantities in the matching quantity group; Perform the following operations on each matching quantity in the matching quantity group: In a combined form, use the matching quantity group and the matching service function sequence corresponding to the matching quantity to obtain a set of matching service function groups, summarize the set of matching service function groups to obtain multiple sets of matching service function groups, and in a permutation form, use the multiple sets of matching service function groups and the scenario text sequence to obtain multiple evaluation service unit sequences.

[0045] Furthermore, the matching service function sequence refers to sequentially extracting the retrieval service function units in the retrieval service function sequence that are the same as the extraction value. For example, the retrieval service function sequence includes a service unit A, a service unit B, a service unit C, and a service unit D, and the preset extraction value is 3. Then the matching service function sequence to be extracted from the retrieval service function sequence using the extraction value is: service unit A, service unit B, and service unit C.

[0046] It can be understood that the matching quantity represents the number of service units required for the same type of service unit to meet the scenario expressed by the scenario recognition text. After first extracting the matching service function groups with the same number as the matching quantity in different matching service function sequences, and then considering the different compatibilities that different matching service function units can adapt to, therefore, by permuting, obtain the different positions of the matching service function units of the same function in the implementation process, and after confirming that the sorted matching service function units can be executed, obtain the evaluation service unit sequence.

[0047] It should be understood that determining the target service unit sequence based on the multiple evaluation service unit sequences includes: Perform the following operations on each evaluation service unit sequence in the multiple evaluation service unit sequences: Obtain the evaluation factor set of the evaluation service unit sequence, and calculate the evaluation reference value using the evaluation factor set. The calculation formula is as follows: Among them, represents the evaluation reference value, represents the preset th coefficient, represents the evaluation factors indicates that there are a total of evaluation factors in the evaluation factor set; Summarize the evaluation reference values to obtain an evaluation reference value set, and use the evaluation reference value set to obtain a target business unit sequence.

[0048] It should be explained that the evaluation factor refers to the index reference for evaluating the evaluation business unit sequence. For example, energy consumption, response time, throughput, concurrency, network bandwidth, encryption strength.

[0049] Furthermore, the obtaining of the target business unit sequence by using the evaluation reference value set includes: Sort the evaluation reference values in the evaluation reference value set in descending order to obtain an evaluation reference value sequence, and use a preset evaluation extraction value to confirm an extraction reference value sequence in the evaluation reference value sequence; Obtain multiple reference comparison sequences based on the extraction reference value sequence, where the reference comparison sequences correspond one-to-one with the evaluation factors, and the order of the reference comparison values in the reference comparison sequence is the same as the order of the evaluation reference values in the extraction reference value sequence; If the first reference comparison value in each reference comparison sequence among the multiple reference comparison sequences is the maximum value, then use the evaluation business unit sequence corresponding to the first extraction reference value in the extraction reference value sequence as the target business unit sequence.

[0050] It should be explained that the method for obtaining the reference value sequence is the same as the method for obtaining the matching business function sequence, which will not be elaborated here. Generally, each evaluation business unit sequence corresponds to an evaluation reference value, and each evaluation reference value corresponds to an evaluation factor set. Therefore, different reference comparison sequences can be obtained by using different evaluation factors. For example, there are three existing evaluation factor sets. Among them, the first evaluation factor set is: 3, 4, 5, the second evaluation factor set is 4, 7, 1, and the third evaluation factor set is: 1, 6, 3, and the evaluation reference value corresponding to the first evaluation factor set is greater than the evaluation reference value corresponding to the second evaluation factor set is greater than the evaluation reference value corresponding to the third evaluation factor set. Then, three reference comparison sequences can be obtained by using these three evaluation factor sets. The three reference comparison sequences are {3, 4, 1}, {4, 7, 6}, and {5, 1, 3} respectively. When the first reference comparison value in each reference comparison sequence among the multiple reference comparison sequences is the maximum value, it means that the first evaluation business unit sequence is superior to other evaluation business unit sequences in all dimensions. The method for obtaining the second matching report is the same as the method for obtaining the first matching report, which will not be elaborated here.

[0051] S6. Use the result feedback unit to send the first matching report or the second matching report to the initiating end of the process orchestration instruction, so as to realize the process orchestration of the payment service.

[0052] To solve the problems described in the background art, the present invention obtains a set of service units marked with service functions, wherein the set of service units includes multiple service units, and each service unit in the multiple service units is marked with a service function. Based on the set of service units and the initial sorting unit, an initial set of service functions is obtained, wherein the initial set of service functions includes multiple initial service function sequences, and the initial service function sequences correspond one-to-one with the service functions. It can be seen that the present invention marks the service units in combination with the text used in the actual situation, so as to facilitate the division and classification of the service units, and screen the service units, screen out the frequently used service units, and evaluate the frequently used service units, so as to clarify the usage order of different service units under the same function in the theoretical situation, laying a foundation for the subsequent orchestration of the payment service. Confirm the receipt of the scene recognition instruction from the scene recognition unit, parse the scene recognition instruction to obtain the scene recognition text, and extract the scene text sequence from the scene recognition text, wherein the scene text sequence includes multiple scene keywords. It can be seen that the present invention combines the specific usage scenario, and through the analysis of the usage scenario, obtains the characterization text for orchestrating different service units. Use the scene text sequence and the initial set of service functions to obtain the matching service unit sequence, drive the matching service unit sequence. If the matching service unit sequence is successfully driven, use the matching service unit sequence to generate the first matching report. Otherwise, use the scene text sequence and the initial set of service functions to obtain multiple evaluated service unit sequences, confirm the target service unit sequence according to the multiple evaluated service unit sequences, and use the target service unit sequence to generate the second matching report. It can be seen that the present invention considers that in the theoretical situation, the orchestration of service units may not meet the compatibility requirements. Therefore, it screens the service units with different functions again, obtains multiple evaluated service unit sequences in a combined form, evaluates the evaluated service unit sequences, and obtains the target service unit sequence after confirming that the optimal evaluated service unit sequence is optimal in all dimensions. And through the form of generating a report, the service units used are clarified, improving the intelligence level of the present invention. Therefore, the present invention can improve the intelligence level of the payment process orchestration.

[0053] As Figure 2 shown, it is a functional module diagram of a visualization-based acquirer payment service process orchestration system provided by an embodiment of the present invention.

[0054] The visualization-based acquiring payment business process orchestration system 100 described in the present invention can be installed in an electronic device. According to the functions achieved, the visualization-based acquiring payment business process orchestration system 100 may include a service unit acquisition module 101, a service scenario recognition module 102, a service unit orchestration module 103, and an orchestration result feedback module 104. The modules described in the present invention may also be referred to as units, which refer to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0055] The service unit acquisition module 101 is configured to receive a process orchestration instruction, and confirm a process orchestration system based on the process orchestration instruction. Among them, the process orchestration system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit; Obtain a service unit set marked with service functions. Among them, the service unit set includes multiple service units, and each service unit in the multiple service units is marked with a service function. Based on the service unit set and the initial sorting unit, obtain an initial service function set. Among them, the initial service function set includes multiple initial service function sequences, and the initial service function sequences correspond to the service functions one by one; The service scenario recognition module 102 is configured to confirm and receive a scenario recognition instruction from the scenario recognition unit, parse the scenario recognition instruction to obtain a scenario recognition text, and extract a scenario text sequence from the scenario recognition text. Among them, the scenario text sequence includes multiple scenario keywords; The service unit orchestration module 103 is configured to obtain a matching service unit sequence by using the scenario text sequence and the initial service function set, drive the matching service unit sequence. If the matching service unit sequence is successfully driven, generate a first matching report by using the matching service unit sequence; Otherwise, obtain multiple evaluation service unit sequences by using the scenario text sequence and the initial service function set, confirm a target service unit sequence according to the multiple evaluation service unit sequences, and generate a second matching report by using the target service unit sequence; The orchestration result feedback module 104 is configured to send the first matching report or the second matching report to the initiator of the process orchestration instruction by using the result feedback unit, so as to implement the process orchestration of the payment service.

[0056] Specifically, each module in the visualization-based acquiring payment business process orchestration system 100 in the embodiment of the present invention adopts the same technical means as those Figure 1 described in the visualization-based acquiring payment business process orchestration method described above, and can produce the same technical effects, which will not be elaborated here.

[0057] 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.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A visualization-based acquirer payment business process orchestration method, characterized in that, The method includes: Receiving a process orchestration instruction, and identifying a process orchestration system based on the process orchestration instruction. The process orchestration system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit; Obtaining a set of business units marked with business functions. The set of business units includes multiple business units, and each business unit in the multiple business units is marked with a business function. An initial set of business functions is obtained based on the set of business units and the initial sorting unit. The initial set of business functions includes multiple initial business function sequences, and the initial business function sequences correspond to the business functions one by one; Confirming to receive a scenario recognition instruction from the scenario recognition unit, parsing the scenario recognition instruction to obtain a scenario recognition text, and extracting a scenario text sequence from the scenario recognition text. The scenario text sequence includes multiple scenario keywords; Using the scenario text sequence and the initial set of business functions to obtain a matching business unit sequence, driving the matching business unit sequence. If the matching business unit sequence is successfully driven, a first matching report is generated using the matching business unit sequence; Otherwise, using the scenario text sequence and the initial set of business functions to obtain multiple evaluated business unit sequences, identifying a target business unit sequence based on the multiple evaluated business unit sequences, and generating a second matching report using the target business unit sequence; Using the result feedback unit to send the first matching report or the second matching report to the initiator of the process orchestration instruction, realizing the process orchestration of the payment business.

2. The method for orchestrating the acquiring payment business process based on visualization according to claim 1, wherein The obtaining of the initial set of business functions based on the set of business units and the initial sorting unit includes: Confirming to receive an initial sorting instruction from the initial sorting unit, parsing the initial sorting instruction to obtain a set of process texts. The set of process texts includes multiple process texts; Performing the following operations on each process text in the set of process texts: Using a pre-built language processing model, a pre-built corpus, and the process text to obtain a sequence of process keywords. The sequence of process keywords includes multiple process keywords; Summarizing the sequences of process keywords to obtain multiple sequences of process keywords, and performing a merging operation on the multiple sequences of process keywords using the corpus to obtain multiple initial function texts; Obtaining an initial set of business functions using the multiple initial function texts and the set of business units.

3. The method for choreographing the acquiring payment service process based on visualization according to claim 2, wherein, The obtaining of the initial set of business functions using the multiple initial function texts and the set of business units includes: Performing the following operations on each initial function text in the multiple initial function texts: Counting the number of times the initial function text appears in the multiple sequences of process keywords to obtain a count, summarizing the counts to obtain a set of counts, and calculating a set of text statistical ratios using the set of counts. The calculation formula is as follows: Among them, represents the th text statistical proportion, represents the th statistical quantity, represents that there are statistical quantities in total in the statistical quantity set, represents the th statistical quantity in the statistical quantity set; Using a preset statistical ratio threshold to extract a set of target statistical ratios from the set of text statistical ratios. The set of target statistical ratios includes multiple target statistical ratios, and the target statistical ratios are greater than or equal to the statistical ratio threshold. Performing the following operations on each target statistical ratio in the multiple target statistical ratios: Update the service functions corresponding to the service units in the service unit set according to the initial function text corresponding to the target statistical ratio to obtain an updated service unit set, where the updated service unit set includes multiple service units marked with updated service functions; Summarize the service units in the updated service unit set according to the updated service functions respectively to obtain multiple classified service unit sets, and use the multiple classified service unit sets to obtain an initial service function set.

4. The method for orchestrating the acquiring payment service process based on visualization according to claim 3, wherein The obtaining the initial service function set by using the multiple classified service unit sets includes: Perform the following operations on each classified service unit in the multiple classified service unit sets: Obtain the average response time of the classified service unit, calculate the unit evaluation value based on the average response time and a pre-constructed unit evaluation relation formula, summarize the unit evaluation values to obtain a unit evaluation value set, sort the unit evaluation values in the unit evaluation value set in descending order to obtain a unit evaluation value sequence; Map the initial service function sequence according to the order of the classified service unit in the unit evaluation value sequence.

5. The visualization-based acquirer payment business process orchestration method according to claim 4, wherein The unit evaluation relational expression is as follows: Among them, represents the unit evaluation value, are all preset coefficients, represents the throughput of the classified business unit, represents the expected throughput of the classified business unit, represents the maximum response time of the classified business unit, represents the average response time of the classified business unit, represents the successful request rate of the classified business unit, represents the average fault diagnosis time of the classified business unit, represents the extended score of the classified business unit.

6. The method for orchestrating the acquiring payment service process based on visualization according to claim 5, wherein The obtaining the matching service unit sequence by using the scenario text sequence and the initial service function set includes: Update the scenario keywords in the scenario text sequence by using multiple initial function texts to obtain an updated scenario keyword sequence; Use the updated scenario keywords in the updated scenario keyword sequence to retrieve a retrieved service function set from the initial service function set, where the retrieved service function set includes multiple retrieved service function sequences; Perform the following operations on each retrieved service function sequence in the multiple retrieved service function sequences: Extract the first retrieved service unit in the retrieved service function sequence, summarize the first retrieved service unit to obtain a retrieved service unit set, and obtain the matching service unit sequence according to the updated scenario keyword sequence and the retrieved service unit set.

7. The method for orchestrating the acquiring payment service process based on visualization according to claim 6, wherein The obtaining multiple evaluated service unit sequences by using the scenario text sequence and the initial service function set includes: Perform the following operations on each retrieved service function sequence in the service function set: Extract the matching service function sequence in the retrieved service function sequence by using a preset extraction value, summarize the matching service function sequences to obtain multiple matching service function sequences; Count the quantity of each scenario text in the scenario text sequence to obtain a matching quantity group, where the matching quantity group is as follows: Among them, represents a matching quantity group, respectively represent the first matching quantity and the second matching quantity in the matching quantity group, represents that there are in total matching quantities in the matching quantity group; Perform the following operations on each matching quantity in the matching quantity group: In a combined form, use the matching quantity group and the matching service function sequence corresponding to the matching quantity to obtain a matching service function group set, summarize the matching service function group sets to obtain multiple matching service function group sets, and in an arranged form, use the multiple matching service function group sets and the scenario text sequence to obtain multiple evaluated service unit sequences.

8. The method for orchestrating the acquiring payment business process based on visualization according to claim 7, characterized in that, The confirming the target service unit sequence according to the multiple evaluated service unit sequences includes: Perform the following operations on each evaluated service unit sequence in the multiple evaluated service unit sequences: Obtain the evaluation factor set of the evaluated service unit sequence, and calculate the evaluation reference value by using the evaluation factor set. The calculation formula is as follows: Among them, represents the evaluation reference value, represents the th preset coefficient, represents the th evaluation factor in the evaluation factor set, represents that there are evaluation factors in the evaluation factor set; Summarize the above evaluation reference values to obtain an evaluation reference value set, and use the evaluation reference value set to obtain a target business unit sequence.

9. The method for orchestrating the acquiring payment business process based on visualization according to claim 8, wherein The step of using the evaluation reference value set to obtain a target business unit sequence includes: Sort the evaluation reference values in the evaluation reference value set in descending order to obtain an evaluation reference value sequence, and use a preset evaluation extraction value to confirm an extraction reference value sequence in the evaluation reference value sequence; Obtain multiple reference comparison sequences based on the extraction reference value sequence, where the reference comparison sequences correspond to the evaluation factors one by one, and the order of the reference comparison values in the reference comparison sequence is the same as the order of the evaluation reference values in the extraction reference value sequence; If the first reference comparison value in each of the multiple reference comparison sequences is the maximum value, then use the evaluation business unit sequence corresponding to the first extraction reference value in the extraction reference value sequence as the target business unit sequence.

10. A visualization-based acquirer payment business process orchestration system, characterized in that, The system includes: A business unit acquisition module, configured to receive a process orchestration instruction, and confirm a process orchestration system based on the process orchestration instruction, where the process orchestration system includes a scenario recognition unit, an initial sorting unit, and a result feedback unit; Obtain a business unit set marked with business functions, where the business unit set includes multiple business units, and each business unit in the multiple business units is marked with a business function. Based on the business unit set and the initial sorting unit, obtain an initial business function set, where the initial business function set includes multiple initial business function sequences, and the initial business function sequences correspond to the business functions one by one; A business scenario recognition module, configured to confirm and receive a scenario recognition instruction from the scenario recognition unit, parse the scenario recognition instruction to obtain a scenario recognition text, and extract a scenario text sequence from the scenario recognition text, where the scenario text sequence includes multiple scenario keywords; A business unit orchestration module, configured to obtain a matching business unit sequence by using the scenario text sequence and the initial business function set, drive the matching business unit sequence, and if the matching business unit sequence is successfully driven, generate a first matching report by using the matching business unit sequence; Otherwise, obtain multiple evaluation business unit sequences by using the scenario text sequence and the initial business function set, confirm a target business unit sequence according to the multiple evaluation business unit sequences, and generate a second matching report by using the target business unit sequence; An orchestration result feedback module, configured to use the result feedback unit to send the first matching report or the second matching report to the initiator of the process orchestration instruction, so as to implement the process orchestration of the payment business.

Images