An information processing method and apparatus

Abstract

The application provides an information processing method, and relates to the technical field of data processing. The method comprises the following steps: analyzing an obtained interaction instruction, and determining a service handling type; calling a service flow knowledge base to perform flow planning according to the service handling type, and generating a target service flow, wherein the service flow knowledge base comprises a plurality of sub-function modules obtained by decoupling an existing service flow, an execution sequence between the sub-function modules, and a handling constraint condition; and performing a service handling operation based on the target service flow. The disclosure can solve the problem of low work efficiency caused by the high dependence of complex service handling on manual operation.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically to an information processing method and apparatus. Background Technology

[0002] As the service industry undergoes a deepening digital transformation, the demand for complex services such as bundled packages and value-added services is increasing. These services typically involve multiple product combinations, complex pricing rules, and strict service agreement processes, and their business logic is highly specialized and complex.

[0003] In related technologies, the handling of the aforementioned complex transactions still heavily relies on manual operation by sales staff. Specifically, sales staff need to manually enter various parameters into the business system based on customer requests, verify key information such as tariff standards, contract terms, and liability for breach of contract, and complete the corresponding system selection and confirmation steps. Because integrated and value-added service businesses involve numerous variables, manual operation is not only time-consuming and inefficient, but also highly susceptible to errors due to sales staff fatigue or negligence.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] In view of the problems existing in the prior art, one of the objectives of the present invention is to provide an information processing method and device, which can at least solve the problem of low work efficiency caused by the high dependence on manual operation in handling complex business.

[0006] To address the aforementioned technical problems, at least one embodiment of this application provides an information processing method, comprising: parsing an acquired interactive instruction to determine a business acceptance type; based on the business acceptance type, invoking a business process knowledge base to perform process planning and generate a target business process, wherein the business process knowledge base includes multiple sub-functional modules decoupled from existing business processes, the execution order of each sub-functional module, and acceptance constraints; and performing a business acceptance operation based on the target business process.

[0007] In one example of this disclosure, the business process knowledge base is constructed in the following manner: based on all business processes in existing business operations, extract the sub-functional modules that are shared by each business and can exist independently, as well as the sub-functional modules that are private to each business; identify and record the execution order between each decomposed sub-functional module, the mutual exclusion relationship and the association relationship between each business, the acceptance channel and the decomposed sub-functional module; associate and store each sub-functional module with its applicable business scenarios, execution order, mutual exclusion relationship and association relationship to form the business process knowledge base.

[0008] In one example of this disclosure, the step of calling the business process knowledge base to perform process planning and generate a target business process according to the business acceptance type includes: determining the required business scenario according to the business acceptance type; retrieving a set of candidate sub-functional modules that match the business scenario from the business process knowledge base; and assembling and generating the target business process according to the execution order and acceptance constraints of each module in the set of candidate sub-functional modules.

[0009] In one example of this disclosure, the method further includes: if the business acceptance type is included in a preset skill library, then calling the atomic interface in the preset skill library corresponding to the business acceptance type to generate the business process.

[0010] In one example of this disclosure, the method further includes: during the execution of the business acceptance operation, if a new interaction instruction is received, the current business process is paused, and the corresponding sub-functional module in the business process knowledge base is invoked according to the new interaction instruction to dynamically adjust the target business process in order to continue to complete the business acceptance.

[0011] In one example of this disclosure, the step of dynamically adjusting the target business process by invoking the corresponding sub-functional module in the business process knowledge base according to the new interaction instruction includes: parsing the new interaction instruction to identify new business requirements or correction intentions; matching the target sub-functional module corresponding to the new business requirements or correction intentions from the business process knowledge base; adding the target sub-functional module to the current position of the target business process, or replacing historical operation nodes in the target business process; and re-verifying and updating the subsequent execution logic of the target business process according to the execution order and acceptance constraints recorded in the business process knowledge base.

[0012] At least one embodiment of this application also provides an information processing apparatus, comprising: an interactive instruction parsing module, configured to parse acquired interactive instructions and determine a business acceptance type; a target business process generation module, configured to, based on the business acceptance type, invoke a business process knowledge base to perform process planning and generate a target business process, wherein the business process knowledge base includes multiple sub-functional modules decoupled from existing business processes, the execution order of each sub-functional module, and acceptance constraints; and a business acceptance operation execution module, configured to execute a business acceptance operation based on the target business process.

[0013] At least one embodiment of this application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the information processing method described above.

[0014] At least one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the information processing method described above.

[0015] At least one embodiment of this application also provides a computer program product, including a computer program that, when executed by a processor, implements the information processing method described above.

[0016] The information processing method provided in the embodiments of this application determines the business acceptance type by parsing the obtained interactive instructions; based on the business acceptance type, it calls a business process knowledge base for process planning to generate a target business process. The business process knowledge base includes multiple sub-functional modules decoupled from existing business processes, the execution order of each sub-functional module, and acceptance constraints; based on the target business process, it executes the business acceptance operation. This disclosure identifies intents and maps them to structured business acceptance types by parsing interactive instructions in real time, and then dynamically generates standardized target business processes by calling a business process knowledge base containing decoupled sub-functional modules, execution order, and acceptance constraints. Finally, based on this target business process, it automatically connects each sub-module to complete the entire automated operation from data filling and link connection to key node prompts, solving the problem of low work efficiency caused by the high dependence on manual operation for complex business acceptance. Attached Figure Description

[0017] Figure 1 A schematic diagram of an exemplary application system architecture for the information processing method in an embodiment of this disclosure is shown. Figure 2 A flowchart of an information processing method according to an embodiment of this disclosure; Figure 3 A flowchart illustrating a specific example of an information processing method according to an embodiment of this disclosure is shown. Figure 4 A flowchart illustrating another specific example of an information processing method according to an embodiment of this disclosure; Figure 5 A flowchart illustrating another specific example of an information processing method according to an embodiment of the present disclosure; Figure 6 A flowchart illustrating yet another specific example of an information processing method according to an embodiment of the present disclosure; Figure 7 A flowchart illustrating yet another specific example of an information processing method according to an embodiment of the present disclosure is shown. Figure 8 A schematic diagram of an information processing device according to an embodiment of this disclosure; Figure 9 A schematic diagram of the structure of the electronic device in the embodiments of this disclosure is shown. Detailed Implementation

[0018] The present invention will be described in detail below through embodiments, but the scope of protection of the present invention is not limited to the following description.

[0019] Unless otherwise specified in the examples, the procedures should be performed under standard conditions or conditions recommended by the manufacturer. Reagents or instruments whose manufacturers are not specified are all commercially available products.

[0020] Example 1 Figure 1 A schematic diagram of an exemplary application system architecture to which the information processing methods of the embodiments of this disclosure can be applied is shown. For example... Figure 1 As shown, the system architecture may include a terminal 101, a network 102, and a server 103.

[0021] Network 102 is a medium used to provide a communication link between terminal 101 and server 103, and can be a wired network or a wireless network.

[0022] Optionally, the aforementioned wireless or wired networks use standard communication technologies and / or protocols. The network is typically the Internet, but can also be any network, including but not limited to Local Area Networks (LANs), Metropolitan Area Networks (MANs), Wide Area Networks (WANs), mobile, wired or wireless networks, private networks, or any combination of virtual private networks. In some embodiments, technologies and / or formats, including Hyper Text Markup Language (HTML), Extensible Markup Language (XML), etc., are used to represent data exchanged over the network. Furthermore, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Networks (VPNs), and Internet Protocol Security (IPSec) can be used to encrypt all or some links. In other embodiments, custom and / or dedicated data communication technologies can be used to replace or supplement the aforementioned data communication technologies.

[0023] Terminal 101 can refer to a physical device deployed near the data source, possessing local computing, storage, and communication capabilities.

[0024] In one example of this disclosure, the terminal parses the obtained interactive instructions to determine the service acceptance type; based on the service acceptance type, it calls the business process knowledge base to perform process planning and generate a target business process, wherein the business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between each sub-functional module, and the acceptance constraints; based on the target business process, the service acceptance operation is executed.

[0025] Server 103 can be a server that provides various services. Optionally, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0026] Those skilled in the art will know that Figure 1The number of terminals, networks, and servers shown is merely illustrative; any number of terminals, networks, and servers can be used as needed. This disclosure does not limit the scope of the embodiments.

[0027] Example 2 Figure 2 A flowchart of an information processing method according to an embodiment of this disclosure is shown, such as... Figure 2 As shown, the information processing method provided in this embodiment includes the following steps: S202, parse the obtained interactive instructions to determine the service acceptance type.

[0028] It should be noted that the aforementioned interactive instructions include at least one of voice instructions, text instructions, or interface operation instructions. The parsing of these interactive instructions involves real-time identification of the business acceptance intent and extraction of key parameters by the central control intelligent agent. The aforementioned business acceptance type can be a specific business processing item code or name that has been identified and categorized and can be automatically executed by intelligent devices.

[0029] In a specific instance, unstructured user intents (such as "I want to upgrade my broadband...") are mapped to structured business terms (such as "Apply for FTTR"), thereby guiding the system to assign appropriate expert agents to perform specific background selection and operation tasks.

[0030] S204. Based on the business acceptance type, call the business process knowledge base to perform process planning and generate the target business process. The business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between the sub-functional modules, and the acceptance constraints.

[0031] It should be noted that the aforementioned sub-functional modules can refer to the smallest independently executable functional units formed by breaking down existing complex and rigid business processes. These sub-functional modules include both common modules shared by various businesses (such as identity authentication and billing) and modules specific to certain businesses. The aforementioned execution order can be defined as the logical dependencies and temporal sequence that each sub-functional module must follow within the business process. The aforementioned acceptance constraints can refer to the restrictive rules or pre- / post-conditions imposed on the execution of sub-functional modules under specific business types or acceptance channels. For example, mobile network services do not require a resource prediction sub-module; channel constraints include: outbound telephone channels do not require "SMS verification code" or "signature confirmation" steps; business constraints include: numerical / rule constraints such as: maximum number of members in a bundled package, FTTR monthly fee not less than X yuan, etc.

[0032] S206, based on the target business process, execute the business acceptance operation.

[0033] It should be noted that the aforementioned target business process can refer to a standardized, automatically executable business processing logic path formed after decoupling, decomposition, orchestration, and constraint definition. For example, when a user initiates a specific business request, the system will retrieve and instantiate the corresponding target business process from the knowledge base based on the characteristics of the request (such as business type and channel), thereby guiding the intelligent agent to automatically connect various sub-modules to complete accurate business processing. The aforementioned execution of business acceptance operations can refer to the system automatically connecting various sub-functional modules according to the pre-planned target business process after the central control intelligent agent identifies the user's intent and the type of business to be processed, completing the fully automated process from data preparation to final completion.

[0034] This disclosure identifies intents by real-time parsing of interactive commands and maps them to structured business acceptance types. It then dynamically generates standardized target business processes by calling a business process knowledge base containing decoupled sub-functional modules, execution order, and acceptance constraints. Finally, based on this target business process, it automatically connects various sub-modules to complete the entire automated operation from data filling and link connection to key node prompts. This achieves flexible decoupling and reuse of complex business processes, precise compliance control based on channel and business characteristics, and solves the problem of low work efficiency caused by the high dependence on manual operation in complex business acceptance. It can significantly reduce the burden of manual operation and improve business processing efficiency.

[0035] In one example disclosed herein, to address the slow response time of large-scale model inference calls, a tiered inference approach is implemented. For high-frequency, complex services (approximately 20% of services, accounting for about 80% of the total cases), a "High-Frequency Complex Service Rule Engine" is constructed. The specific implementation is as follows: First, based on user interaction input, keywords related to service acceptance are parsed. For standardized expressions, keywords can be directly extracted. For colloquial expressions, a lightweight service acceptance distillation model is built to uniformly convert users' colloquial and fragmented statements into standard system intent text (e.g., "I want to apply for high-speed broadband" is standardized to "Apply for FTTR"). Only information extraction is performed; no modification or additional text generation is performed. Second, based on the parsed keywords, the "High-Frequency Complex Service Rule Engine" is invoked to match the service acceptance process, completing the acceptance interaction in milliseconds. This replaces the excessively long contextual inference of the general large model, solving the problem of excessive inference latency and optimizing the salesperson experience. For low-frequency, complex services (approximately 80% of services, accounting for about 20% of the total cases), the large model continues to be used for inference analysis, parsing intent and determining service acceptance types. Because it is less frequently used, the frequency of calling the large model is reduced, the computing power of a single task is sufficient, and the inference is correspondingly faster. Third, based on changes in the business being handled, a high-frequency and complex business identification model is constructed. This model is based on the product lifecycle, including newly launched products, mainstream products, best-selling products, and products nearing their expiration date. It further breaks down the online, offline, and platform order volumes for the past six months across various scenarios such as campuses, individuals, integrated services, and merchants. This model distinguishes between valid orders, potential inquiries, and order cancellations. A combination of Analytic Hierarchy Process (AHP) (subjective business weighting) and entropy weighting (objective data weighting) is used for weighting, taking into account both business management orientation and the patterns in real work order data. The weighted calculation outputs a list of high-frequency businesses, and the "high-frequency and complex business rule engine" is dynamically iterated and updated to better adapt to actual front-line production.

[0036] In one embodiment of this disclosure, such as Figure 3 As shown, the information processing method provided in this embodiment can construct a business process knowledge base through the following steps: S302, based on all existing business processes, extract the sub-functional modules that are shared by each business and can exist independently, as well as the sub-functional modules that are used privately by each business.

[0037] For example, extract all business processes from the existing business operation support system. The system automatically analyzes each business process and extracts the sub-functional modules that can exist independently and the private sub-functional modules that are shared by each business. The sub-functional modules mainly include: customer identity authentication, overdue payment verification, product package selection, add-on package selection, number selection, resource prediction, signature confirmation, SMS verification code confirmation, SMS reply confirmation, payment, and form printing without filling out forms, etc.

[0038] S304 identifies and records the execution order of each disassembled sub-functional module, the mutual exclusion relationship and the correlation relationship between each service, acceptance channel and the disassembled sub-functional module.

[0039] For example, the system automatically analyzes and identifies all business processes in the existing system, and automatically identifies and records the execution order of each decomposed sub-functional module. Examples include: customer authentication, overdue payment verification, resource prediction, number selection; product package selection, form printing without filling out forms, signature confirmation; SMS verification code confirmation, SMS reply confirmation, and payment.

[0040] S306 associates and stores each sub-functional module with its applicable business scenarios, execution order, mutual exclusion relationships, and related relationships to form a business process knowledge base.

[0041] For example, the above information can be linked and recorded to record the applicable business scenarios, order of application, acceptance constraints, and other usage restrictions and applicable businesses for each sub-functional module, forming a business process knowledge base.

[0042] This disclosure constructs a knowledge base by extracting shared and private sub-functional modules and associating their execution order, mutual exclusion, and relationships. This enables atomic decomposition and high reusability of business processes, and supports dynamic and flexible orchestration of processes based on business scenarios and channels. As a result, while ensuring business compliance and accuracy, it significantly improves the system's adaptability to multi-scenario business and maintenance efficiency.

[0043] In one embodiment of this disclosure, such as Figure 4 As shown, the information processing method provided in this embodiment of the disclosure, which calls the business process knowledge base to perform process planning and generate the target business process according to the business acceptance type, includes the following steps: S402, determine the required business scenario based on the business acceptance type.

[0044] For example, the system can acquire interactive commands input by sales staff in real time, parse the required service type and input parameters, and assign expert agents to execute them. A salesperson or user might describe the service they need in a single sentence (e.g., "My number is 155XXX, I want to purchase a 129 yuan ice cream bundled package and activate 500M broadband"), and the system receives this input. It also supports input via voice, images, and other methods. Based on the information received by the command receiving module, the system parses the information required for service processing. To parse the service type, the system first parses, standardizes, and vectorizes the information, enabling precise matching with the vectorized interactive corpus in the knowledge base. Then, relying on the mapping relationship of "user's original expression—user's intent (service processing or consultation)—service type" in the knowledge base, the system accurately identifies the user's core needs and clarifies the type of service the user wants to process, providing a reliable basis for the subsequent precise assignment of tasks to the expert agent. For example, if a user states in colloquial language, "My number is XXXX, and I'm currently on a bundled package with broadband, but the speed is too slow and the signal coverage is poor. Is there a solution?", the system can accurately identify the core intent as "Service application - install FTTR on the regular broadband in the bundled package for the XXXX number," ensuring accurate task assignment. Furthermore, based on the information received by the instruction receiving module, the system can extract keywords from the instruction to determine the required service number, product package information, etc. Additionally, based on the user intent recognition results, the system can intelligently assign appropriate expert agents for processing and simultaneously push the human-computer interaction input and the input parameter information recognized by the system.

[0045] S404, retrieve a set of candidate sub-functional modules that match the business scenario from the business process knowledge base; S406. Based on the execution order and acceptance constraints of each module in the candidate sub-functional module set, assemble and generate the target business process.

[0046] In a specific example, based on the planned business process and the necessary user information (such as business number, product package information, etc.) included in the salesperson's instructions, the system retrieves and matches similar service slips from the historical service slip database; the system compares the templates of similar service slips and fills in the relevant service information (such as package, number, required services, developer, etc.); the system automatically follows the planned process, automatically simulating manual connection of each sub-functional module, performing step-by-step automatic operations, and realizing automatic connection between sub-processes; after the "print without filling out the form" operation is executed, the system pops up a prompt for the salesperson or automatically broadcasts relevant matters that need to be emphasized to the user (such as the effective time of adding a member, fees, etc.).

[0047] This disclosure achieves automated and standardized generation of the target business process by accurately locating the business scenario based on the business acceptance type, retrieving a matching set of sub-functional modules from the knowledge base, and then assembling them according to a strict execution order and acceptance constraints. This ensures the correctness and compliance of the process logic and improves the efficiency and accuracy of process planning.

[0048] In one example disclosed herein, to address the issue of AI illusions easily leading to errors in the processing of applications: During the application processing stage, to prevent AI illusions from arbitrarily filling in information, a verification mechanism is added. This mechanism links to "the entire domain's historical business processing order records" to verify the content entered by the AI ​​digital salesperson against the actual processing data. It accurately identifies false, inconsistent, and abnormal information generated by AI illusions, tiered push notifications of suspicious points, and mandates manual review and confirmation before the application can be completed. The specific modeling process for the business processing verification model is as follows: The business unit is disassembled at the machine layer to achieve verification during execution. Using the smallest functional granularity as the cutting standard, the business acceptance process is modularly decomposed, divided into independent verification units, and the fixed verification dimensions of each unit are unified and solidified to build a point-to-point block verification architecture. The decomposed units include standardized functional modules such as customer authentication, package product selection, developer information entry, supplementary product selection, and contract plan selection. The benchmark data construction layer relies on the current mobile phone number, customer documents, installation address, and processing channel core primary keys to accurately retrieve historical formal business acceptance orders that have been completed, are compliant and valid, and have not been cancelled or invalidated for the customer, channel, and the same business category, and aggregates them to generate a standardized compliance benchmark dataset. The anomaly detection layer uses the benchmark data source as a reference to match and compare the required fields in the execution of the acceptance process, identify and mark anomalies and AI that deviate from historical orders. Hallucination-related abnormal information; a manual confirmation layer for suspicious points, where the system highlights suspicious content in modules and issues pop-up warnings; the suspicious point can only be unlocked after manual verification, modification, and confirmation; a process risk control blocking layer, where submissions cannot take effect without historical orders from the same source or without manual confirmation, thus preventing AI-generated hallucination-related false information from being directly implemented and avoiding risks of operational errors and violations in business processing.

[0049] In one embodiment of this disclosure, such as Figure 5 As shown, the information processing method provided in this embodiment further includes the following steps: S502 If the business acceptance type is included in the preset skill library, then the atomic interface corresponding to the business acceptance type in the preset skill library is called to generate the business process.

[0050] In a specific example, if the required business type (business acceptance type) is already included in the preset skill library: relying on the skills in the built-in preset skill library, the high-frequency and complex business acceptance process is encapsulated into an independent and reusable atomic interface. When receiving a command from the central control agent to accept such a business, the corresponding skill can be directly invoked to quickly and autonomously plan the business process. If it is not included in the preset skill library, after determining the business acceptance type, the business process knowledge base is invoked to plan the process and generate the target business process.

[0051] This disclosure introduces a pre-defined skill library to directly map common or standardized business acceptance types to corresponding atomic interfaces to automatically generate business processes, avoiding repetitive process planning and assembly work. This significantly improves the processing efficiency and response speed of high-frequency and standard businesses, while ensuring the consistency and stability of basic business logic.

[0052] In one embodiment of this disclosure, such as Figure 6 As shown, the information processing method provided in this embodiment further includes the following steps: S602: During the execution of business acceptance operation, if a new interactive instruction is received, the current business process is paused, and the corresponding sub-functional module in the business process knowledge base is called according to the new interactive instruction to dynamically adjust the target business process in order to continue to complete the business acceptance.

[0053] For example, the system can suspend the current process at any time based on real-time changes in user needs, flexibly switching between different expert agents to ensure service continuity and flexibility. Specifically, if user needs change temporarily during business processing (such as temporarily adding a secondary card), the central control agent can temporarily interrupt the current workflow, switch to another expert agent for execution, and then switch back to the original expert agent to continue subsequent operations from the point of interruption after execution is completed.

[0054] This disclosure achieves high flexibility and real-time adaptability in business processing by responding to new interactive instructions and dynamically adjusting business processes during execution. It can accurately meet users' sudden personalized needs or correct operational deviations, thereby significantly improving user experience and the success rate of business acceptance.

[0055] In one embodiment of this disclosure, such as Figure 7 As shown, the information processing method provided in this embodiment of the disclosure, which calls the corresponding sub-functional module in the business process knowledge base according to the new interaction instruction to dynamically adjust the target business process, includes the following steps: S702, parses new interaction commands and identifies new business requirements or correction intentions; S704, Match the target sub-functional module corresponding to the new business requirement or the intention to modify from the business process knowledge base; S706, add the target sub-functional module to the current position of the target business process, or replace the historical operation node in the target business process; S708, based on the execution order and acceptance constraints between sub-functional modules recorded in the business process knowledge base, re-verify and update the subsequent execution logic of the target business process.

[0056] In a specific instance, during the intelligent processing of a certain expert agent, if a user raises a new request, the current process can be paused at any time according to the instructions of the central control agent. After receiving the new instructions from the central control agent, another expert agent is invoked to autonomously plan a sub-process (such as calling the sub-module corresponding to the new instructions in the business processing knowledge base, supplementing the sub-process or correcting historical operation information), merging them into a new process, and then executing the processing operation. If a user wants to open a new secondary SIM card while the converged service expert AI agent has already planned and executed the processing, the following steps are taken: The salesperson inputs the instruction "Open a new secondary SIM card and include it in this converged service package"; the headquarters AI agent parses the instruction and determines "Open a new mobile network SIM card and include it in the converged service package"; the mobile network business expert AI agent is invoked to plan the process, and by calling the sub-module corresponding to the new instruction in the dedicated knowledge base, the original planned process is corrected. Specifically, at the "Add converged member" position, the "Open a new mobile network secondary SIM card" sub-module is inserted, and a new process is planned; intelligent processing is executed. In this step, the current execution of the converged service expert AI agent is paused to determine if the current execution position is after "Add converged member". If so, the operation is rolled back to the step before "Add converged member" submission, and the central control AI agent is notified to switch to the mobile network expert AI agent to execute "Open a new mobile network secondary SIM card". After execution, the mobile network expert AI agent notifies the central control AI agent to switch back to the converged service expert AI agent, and execution continues from the breakpoint until completion.

[0057] This embodiment enables flexible addition or replacement of business processes by accurately parsing interaction intents and intelligently matching sub-functional modules. At the same time, it re-verifies subsequent logic based on strict execution order and constraints, ensuring the integrity, compliance, and correctness of the dynamically adjusted process. This allows the system to meet users' real-time change requirements while ensuring the robust operation of business processing.

[0058] Example 3 Based on the same inventive concept, this disclosure also provides two information processing devices, as described in the following embodiments. Since the principle by which these devices solve the problem is similar to that of the method embodiments described above, the implementation of these devices can refer to the implementation of the method embodiments described above, and repeated details will not be repeated.

[0059] Figure 8A schematic diagram of an information processing apparatus according to an embodiment of the present disclosure is shown, such as... Figure 8 As shown, the device includes: an interactive instruction parsing module 81, a target business process generation module 82, and a business acceptance operation execution module 83.

[0060] Among them, the interactive instruction parsing module 81 is used to parse the obtained interactive instructions and determine the service acceptance type; The target business process generation module 82 is used to call the business process knowledge base to perform process planning and generate the target business process according to the business acceptance type. The business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between the sub-functional modules, and the acceptance constraints. The business acceptance operation execution module 83 is used to execute business acceptance operations based on the target business process.

[0061] In one example of this disclosure, the business process knowledge base in the aforementioned information processing device is constructed in the following manner: based on all business processes in the existing business operations, extract the sub-functional modules that are shared by each business and can exist independently, as well as the sub-functional modules that are private to each business; identify and record the execution order between each disassembled sub-functional module, the mutual exclusion relationship and the association relationship between each business, the acceptance channel and the disassembled sub-functional module; and associate and store each sub-functional module with its applicable business scenarios, execution order, mutual exclusion relationship and the association relationship to form a business process knowledge base.

[0062] In one example of this disclosure, the target business process generation module 82 is further configured to: determine the required business scenario based on the business acceptance type; retrieve a set of candidate sub-functional modules that match the business scenario from the business process knowledge base; and assemble and generate the target business process according to the execution order and acceptance constraints of each module in the candidate sub-functional module set.

[0063] In one example of this disclosure, the information processing device further includes a skill library module, which is used to call the atomic interface in the preset skill library corresponding to the business acceptance type to generate a business process if the business acceptance type is included in the preset skill library.

[0064] In one example of this disclosure, the information processing device further includes an adjustment module, which, during the execution of a business acceptance operation, if a new interactive instruction is received, pauses the current business process and, based on the new interactive instruction, calls the corresponding sub-functional module in the business process knowledge base to dynamically adjust the target business process in order to continue completing the business acceptance.

[0065] In one example of this disclosure, the aforementioned adjustment module is further configured to: parse new interactive instructions to identify new business requirements or correction intentions; match target sub-functional modules corresponding to the new business requirements or correction intentions from the business process knowledge base; add the target sub-functional modules to the current position of the target business process, or replace historical operation nodes in the target business process; and re-verify and update the subsequent execution logic of the target business process according to the execution order and acceptance constraints recorded in the business process knowledge base.

[0066] It should be noted that the interactive instruction parsing module 81, the target business process generation module 82, and the business acceptance operation execution module 83 mentioned above correspond to S202 to S206 in the method embodiment. The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above method embodiment. It should be noted that the above modules, as part of the apparatus, can be executed in a computer system such as a set of computer-executable instructions.

[0067] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0068] Example 4 The following reference Figure 9 To describe an electronic device 900 according to such an embodiment of the present disclosure. Figure 9 The electronic device 900 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0069] like Figure 9 As shown, the electronic device 900 is manifested in the form of a general-purpose computing device. The components of the electronic device 900 may include, but are not limited to: at least one processing unit 910, at least one storage unit 920, and a bus 930 connecting different system components (including storage unit 920 and processing unit 910).

[0070] The storage unit stores program code that can be executed by the processing unit 910, causing the processing unit 910 to perform the steps described in the "Exemplary Methods" section above according to various exemplary embodiments of this disclosure.

[0071] For example, the processing unit 910 can execute the following steps in the above method embodiment: parse the obtained interactive instructions to determine the business acceptance type; according to the business acceptance type, call the business process knowledge base to perform process planning and generate a target business process, wherein the business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between each sub-functional module, and acceptance constraints; and execute the business acceptance operation based on the target business process.

[0072] For example, the processing unit 910 can execute the following steps in the above method embodiment: based on all business processes in the existing business operation, extract the sub-functional modules that can exist independently and those that are used privately by each business; identify and record the execution order between each disassembled sub-functional module, the mutual exclusion relationship and the association relationship between each business, the acceptance channel and the disassembled sub-functional module; associate and store each sub-functional module with its applicable business scenarios, execution order, mutual exclusion relationship and association relationship to form a business process knowledge base.

[0073] For example, the processing unit 910 can perform the following steps in the above method embodiment: determine the required business scenario according to the business acceptance type; retrieve a set of candidate sub-functional modules that match the business scenario in the business process knowledge base; and assemble and generate the target business process according to the execution order and acceptance constraints of each module in the candidate sub-functional module set.

[0074] For example, the processing unit 910 can execute the following steps of the above method embodiment: if the business acceptance type is included in the preset skill library, then the atomic interface corresponding to the business acceptance type in the preset skill library is called to generate the business process.

[0075] For example, the processing unit 910 can execute the following steps of the above method embodiment: during the execution of the business acceptance operation, if a new interaction instruction is received, the current business process is paused, and the corresponding sub-functional module in the business process knowledge base is called according to the new interaction instruction to dynamically adjust the target business process in order to continue to complete the business acceptance.

[0076] For example, the processing unit 910 may execute the following steps in the above method embodiment: parse the new interactive instruction and identify the new business requirement or correction intention; match the target sub-functional module corresponding to the new business requirement or correction intention from the business process knowledge base; add the target sub-functional module to the current position of the target business process, or replace the historical operation node in the target business process; and re-verify and update the subsequent execution logic of the target business process according to the execution order and acceptance constraints recorded in the business process knowledge base.

[0077] Storage unit 920 may include readable media in the form of volatile storage units, such as random access memory (RAM) 9201 and / or cache 9202, and may further include read-only memory (ROM) 9203.

[0078] The storage unit 920 may also include a program / utility 9204 having a set (at least one) program module 9205, such program module 9205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0079] Bus 930 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0080] Electronic device 900 can also communicate with one or more external devices 940 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 900, and / or with any device that enables electronic device 900 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 950. Furthermore, electronic device 900 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 960. As shown, network adapter 960 communicates with other modules of electronic device 900 via bus 930. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0081] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0082] Example 5 In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. A program product capable of implementing the methods described above is stored thereon. In some possible implementations, various aspects of this disclosure may also be implemented as a program product including program code, which, when run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0083] More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0084] In this disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of transmitting, propagating, or transmitting a program for use by or in connection with an instruction execution system, apparatus, or device.

[0085] Optionally, the program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0086] In practical implementation, program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0087] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units. Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0088] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0089] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

[0090] Example 6 Another embodiment of this application relates to a computer program product, including a computer program. When executed by a processor, the computer program implements the method embodiments described above.

[0091] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0092] Furthermore, although the steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0093] It should be noted that the embodiments described above are only for explaining the present invention and do not constitute any limitation on the present invention. The present invention has been described with reference to typical embodiments, but it should be understood that the words used therein are descriptive and explanatory terms, not limiting terms. Modifications can be made to the present invention within the scope of the claims, and revisions can be made to the present invention without departing from the scope and spirit of the present invention. Although the present invention described herein relates to specific methods, materials, and embodiments, it does not mean that the present invention is limited to the specific examples disclosed herein; on the contrary, the present invention can be extended to all other methods and applications with the same function.

Claims

1. An information processing method, characterized in that, include: Parse the obtained interaction instructions to determine the type of service accepted; Based on the business acceptance type, the business process knowledge base is invoked to perform process planning and generate the target business process. The business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between the sub-functional modules, and the acceptance constraints. Based on the target business process, perform the business acceptance operation.

2. The information processing method according to claim 1, characterized in that, The business process knowledge base is constructed in the following ways: Based on all existing business processes, extract the sub-functional modules that can exist independently and those that are shared by each business, as well as the sub-functional modules that are used privately by each business. Identify and record the execution order of each decomposed sub-functional module, the mutual exclusion relationship and the correlation relationship between each business, acceptance channel and the decomposed sub-functional module; Each sub-functional module is associated with and stored in relation to its applicable business scenarios, execution order, mutual exclusion relationships, and related relationships, forming the business process knowledge base.

3. The information processing method according to claim 1, characterized in that, The step of calling the business process knowledge base to perform process planning and generate the target business process based on the business acceptance type includes: Determine the required business scenario based on the business acceptance type; Retrieve a set of candidate sub-functional modules that match the business scenario from the business process knowledge base; The target business process is generated by assembling the modules in the candidate sub-functional module set according to their execution order and acceptance constraints.

4. The information processing method according to claim 1, characterized in that, The method further includes: If the business acceptance type is included in the preset skill library, then the atomic interface corresponding to the business acceptance type in the preset skill library is called to generate the business process.

5. The information processing method according to any one of claims 1 to 4, characterized in that, The method further includes: If a new interaction instruction is received during the execution of the business acceptance operation, the current business process is paused, and the corresponding sub-functional module in the business process knowledge base is invoked according to the new interaction instruction to dynamically adjust the target business process in order to continue to complete the business acceptance.

6. The information processing method according to claim 5, characterized in that, The step of dynamically adjusting the target business process by invoking the corresponding sub-functional module in the business process knowledge base according to the new interaction instruction includes: Analyze the new interactive instructions to identify new business requirements or correction intentions; Match the target sub-functional module corresponding to the new business requirement or modification intention from the business process knowledge base; Add the target sub-functional module to the current position of the target business process, or replace the historical operation node in the target business process; Based on the execution order and acceptance constraints of the sub-functional modules recorded in the business process knowledge base, the subsequent execution logic of the target business process is re-verified and updated.

7. An information processing device, characterized in that, include: The interactive instruction parsing module is used to parse the acquired interactive instructions and determine the service acceptance type. The target business process generation module is used to call the business process knowledge base to perform process planning and generate the target business process according to the business acceptance type. The business process knowledge base includes multiple sub-functional modules decoupled from the existing business process, the execution order between the sub-functional modules, and the acceptance constraints. The business acceptance operation execution module is used to execute business acceptance operations based on the target business process.

8. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the information processing method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the information processing method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the information processing method according to any one of claims 1 to 6.

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