Business processing method, electronic equipment, readable storage medium and program product
By deduplication and grouping the preset rules of the intelligent virtual housekeeper, the target rules are determined and the corresponding actions are performed, the problem of low business processing efficiency caused by hard coding is solved, and flexible and efficient business processing is achieved.
Patent Information
- Application Number
- CN202510352587.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-24
- Publication Date
- 2025-07-29
AI Technical Summary
In the prior art, intelligent virtual housekeepers use hard-coded methods to implement rule logic during intelligent dialogue, resulting in low business processing efficiency and difficulty in dynamic adjustment to adapt to the needs of different business scenarios.
By determining the target rules corresponding to the business scenario from multiple preset rules, deduplication and grouping of preset conditions, obtaining business data based on the deduplication conditions and determining whether the target rules are met, and performing corresponding preset actions.
Improve business processing efficiency, reduce the judgment of redundant conditions and the amount of data, simplify logic, ensure smooth business progress, and adapt to the needs of different business scenarios.
Smart Images
Figure CN120386797A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to technical fields such as rule engines and intelligent conversations. In particular, the present disclosure relates to a service processing method, an electronic device, a readable storage medium, and a program product. Background Art
[0002] With the development of computer technology, more and more technologies are applied in the rental field. For example, an intelligent virtual butler is pre-designed, and then the intelligent virtual butler can have an intelligent conversation with the user to automatically help the user handle rental-related issues.
[0003] In the related art, the rules adopted by the intelligent virtual butler during the intelligent conversation are implemented in a hard-coded manner. Hard coding usually means that the rule logic is directly written in the code. This structure is relatively fixed and difficult to dynamically adjust, which will lead to low service processing efficiency. Summary of the Invention
[0004] The present disclosure provides a service processing method, an electronic device, a readable storage medium, and a program product.
[0005] According to one aspect of the present disclosure, a service processing method is provided, including: Determining a plurality of target rules corresponding to a service scenario from a plurality of preset rules, wherein each of the plurality of target rules includes at least one preset condition and a preset action; Removing duplicates from at least one preset condition of the plurality of target rules to obtain deduplicated conditions; Obtaining service data based on the deduplicated conditions, and determining whether the service data satisfies the deduplicated conditions to obtain a determination result; Determining the target rules satisfied by the service data according to the determination result; and Executing the preset actions corresponding to the target rules satisfied by the service data.
[0006] According to the service processing method of at least one embodiment of the present disclosure, removing duplicates from at least one preset condition of the plurality of target rules to obtain deduplicated conditions includes: Grouping at least one preset condition of the plurality of target rules based on the variables associated with the preset conditions to obtain multiple groups of preset conditions, wherein the variables associated with the multiple groups of preset conditions are different from each other; and Removing the duplicate preset conditions from each of the multiple groups of preset conditions respectively to obtain multiple groups of the deduplicated conditions.
[0007] According to the service processing method of at least one embodiment of the present disclosure, grouping at least one preset condition of the plurality of target rules based on the variables associated with the preset conditions to obtain multiple groups of preset conditions includes: Group at least one preset condition of the multiple target rules in a way of dividing a group by a variable, to obtain multiple groups of preset conditions.
[0008] According to the service processing method of at least one embodiment of the present disclosure, the deduplicated conditions include multiple groups; Judge whether the service data meets the deduplicated conditions, to obtain a judgment result, including: Determine the priorities of multiple groups of deduplicated conditions; and Based on the priorities, sequentially judge whether the service data meets the multiple groups of deduplicated conditions, to obtain the judgment result.
[0009] According to the service processing method of at least one embodiment of the present disclosure, the variables associated with multiple groups of deduplicated conditions are different from each other, and each group of deduplicated conditions is associated with one variable; Determine the priorities of multiple groups of deduplicated conditions, including: Based on the mapping relationship between preset priorities and preset variables, determine the priorities corresponding to the variables associated with the multiple groups of deduplicated conditions; and Take the priorities corresponding to the variables associated with the multiple groups of deduplicated conditions as the priorities of the multiple groups of deduplicated conditions.
[0010] According to the service processing method of at least one embodiment of the present disclosure, the service data includes data values of variables associated with multiple groups of deduplicated conditions; Based on the priorities, sequentially judge whether the service data meets the multiple groups of deduplicated conditions, to obtain the judgment result, including: For each group of deduplicated conditions in the multiple groups of deduplicated conditions, add the deduplicated conditions in this group of deduplicated conditions that are met by the data value of the variable associated with this group of deduplicated conditions to the judgment result.
[0011] According to the service processing method of at least one embodiment of the present disclosure, the judgment result includes the deduplicated conditions met by the service data; Determine the target rules met by the service data according to the judgment result, including: Combine the deduplicated conditions met by the service data to obtain multiple combined rules; and Take the combined rule that is the same as the target rule as the target rule met by the service data.
[0012] According to another aspect of the present disclosure, there is provided an electronic device, including: a memory that stores execution instructions; and a processor that executes the execution instructions stored in the memory, so that the processor executes the service processing method of any one embodiment of the present disclosure.
[0013] According to another aspect of the present disclosure, there is provided a readable storage medium in which execution instructions are stored, and when the execution instructions are executed by a processor, they are used to implement the service processing method of any embodiment of the present disclosure.
[0014] According to yet another aspect of the present disclosure, there is provided a computer program product including a computer program, and when the computer program is executed by a processor, it implements the service processing method of any embodiment of the present disclosure. Description of the Drawings
[0015] The drawings illustrate exemplary embodiments of the present disclosure and, together with the description thereof, are used to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are included in this specification and form a part of this specification.
[0016] Figure 1 It is a flowchart of the service processing method of an embodiment of the present disclosure.
[0017] Figure 2 It is a visualization example diagram of the preset rule storage structure of an embodiment of the present disclosure.
[0018] Figure 3 It is a process schematic diagram of obtaining the deduplicated conditions of an embodiment of the present disclosure.
[0019] Figure 4 It is a process schematic diagram of obtaining the judgment result of an embodiment of the present disclosure.
[0020] Figure 5 It is a process schematic diagram of determining the priority of an embodiment of the present disclosure.
[0021] Figure 6 It is a process schematic diagram of determining the target rules to be satisfied of an embodiment of the present disclosure.
[0022] Figure 7 It is a flowchart of the service processing method of another embodiment of the present disclosure.
[0023] Figure 8 It is a visualization example diagram of the service processing method of an embodiment of the present disclosure.
[0024] Figure 9 It is a structural schematic block diagram of the service processing device of an embodiment of the present disclosure.
[0025] Figure 10 It is a structural schematic block diagram of an electronic device of an embodiment of the present disclosure. Detailed Embodiments
[0026] The present disclosure will be further described in detail below in conjunction with the accompanying drawings and examples. It can be understood that the specific examples described herein are only used to explain the relevant content and do not limit the present disclosure. Additionally, it should be noted that for ease of description, only parts related to the present disclosure are shown in the accompanying drawings.
[0027] It should be noted that, without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The technical solutions of the present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.
[0028] In the related art, the rules adopted by the intelligent virtual butler during the intelligent conversation process are implemented in a hard-coded manner. Hard coding usually means that the rule logic is directly written in the code, and this structure is relatively fixed and difficult to dynamically adjust. However, the rules required to be matched in different business scenarios may be different. For example, in the rental chat scenario, 100 rules may need to be matched, in the automatic work order closing scenario, only 10 rules may need to be matched, and in the timed task (such as timed price adjustment) scenario, only 50 rules may need to be matched. If the hard-coded method is used, then regardless of which business scenario, 100 rules need to be matched, which will result in unnecessary rule matching, wasting resources and reducing the business processing efficiency.
[0029] Therefore, the present disclosure proposes a business processing method.
[0030] The business processing method of the present disclosure can be used for an electronic device to match business data through different target rules in different business scenarios, so as to execute the preset actions corresponding to the target rules satisfied by the business data. In the present disclosure, the electronic device includes but is not limited to mobile phones, tablet computers, laptop computers, personal computers, wearable devices, teller machines, etc.
[0031] For ease of description and to make the technical solutions of the specific embodiments of the present disclosure easier to understand, before describing the business processing method implemented in the present disclosure, the technical terms involved in the specific embodiments of the present disclosure are explained as follows: A rule engine is a software component used to automatically execute decisions according to predefined rules, so as to achieve the efficient management and execution of complex logic.
[0032] A rule is a set of conditions and corresponding actions. When specific conditions are met, the system will automatically execute the corresponding actions to achieve the expected business goals.
[0033] Figure 1 The overall flowchart of the business processing method M100 according to an embodiment of the present disclosure is shown. As Figure 1The method shown includes steps S110 to S150. Among them, the method can be executed by electronic devices such as servers, mobile phones, and computers.
[0034] Specifically, Figure 1 the method shown includes: S110. Determine multiple target rules corresponding to the business scenario from multiple preset rules, where each of the multiple target rules includes at least one preset condition and a preset action; The preset rules can be pre-configured by relevant personnel. Exemplarily, after the preset rules are configured, the business scenarios applicable to each preset rule can be configured, and a mapping relationship between the preset rules and the preset business scenarios can be generated. Furthermore, the electronic device can automatically determine multiple target rules corresponding to the business scenario according to this mapping relationship.
[0035] The target rules corresponding to different business scenarios may not be completely the same or may be completely different, which is not limited here. The electronic device can automatically determine the business scenario when receiving the conversation information input by the user, or can automatically determine the business scenario at a certain period, which is not limited here. Business scenarios include, but are not limited to, rental chat scenarios, automatic work order closing scenarios, and timed task (such as timed price adjustment) scenarios, etc.
[0036] Please combine Figure 2 , in an example, multiple preset rules are stored in a tree structure. In this tree structure, under the root node, there are two branches according to different system ids (serverIds), namely Cloud Steward and Service Steward; under Cloud Steward, there are three groups according to different parameters, namely City, Source, and Intention. Among them, the City group corresponds to preset rules 1 to 6, the Source group corresponds to preset rules 11 to 16, and the Intention group corresponds to preset rules 21 to 26; under Service Steward, there are two groups according to different parameters, namely Housing Source and Identity. Among them, the Housing Source group corresponds to preset rules 31 to 36, and the Identity group corresponds to preset rules 41 to 46. All the preset rules in this tree structure are at least partially different from each other. The preset rules in the City group at least include preset conditions with the city as a variable, the preset rules in the Source group at least include preset conditions with the source as a variable, and so on. If the preset rules for the rental chat scenario corresponding to the City group, Source group, and Intention group in the Cloud Steward system are pre-configured, then in the rental chat scenario of the Cloud Steward system, preset rules 1 to 6, 11 to 16, and 21 to 26 will be used as target rules; if the preset rules for the automatic work order closing scenario corresponding to the Source group in the Cloud Steward system are pre-configured, then in the automatic work order closing scenario of the Cloud Steward system, preset rules 11 to 16 will be used as target rules; if the preset rules for the timed task scenario corresponding to the City group and Intention group in the Cloud Steward system are pre-configured, then in the timed task scenario of the Cloud Steward system, preset rules 1 to 6 and 21 to 26 will be used as target rules.
[0037] The preset conditions include, but are not limited to, the data values of variables being within a preset range or at a preset value. For example, the city code is 50100, the source is 1, the number of available housing units is greater than 1, etc.
[0038] The preset actions include, but are not limited to, adjusting the price, exposing the housing source, replying with a preset text, etc.
[0039] It can be understood that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.
[0040] For example, when responding to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that executes the operations of the technical solutions of the present disclosure according to the prompt message.
[0041] As an optional but non-limiting implementation manner, when responding to receiving an active request from a user, the manner of sending a prompt message to the user can be, for example, in the form of a pop-up window, and the prompt message can be presented in text in the pop-up window. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.
[0042] It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not limit the implementation manners of the present disclosure. Other manners that meet relevant laws and regulations can also be applied to the implementation manners of the present disclosure.
[0043] At the same time, it can be understood that the data involved in the technical solutions of the present disclosure (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of corresponding laws, regulations and related provisions.
[0044] It should be noted that the specific numerical values mentioned above are only used as examples to illustrate the embodiments of the present disclosure in detail and should not be construed as a limitation of the present disclosure. In other examples, implementation manners or embodiments, other numerical values can be selected according to the present disclosure, and no specific limitation is made here.
[0045] S120. Remove duplicates from at least one preset condition of multiple target rules to obtain the de-duplicated condition; There are numerous target rules, and it is inevitable that some of the preset conditions of some target rules are the same. If the same preset conditions participate in the judgment repeatedly, it will cause unnecessary waste of resources. By deduplication, the number of the same preset conditions can be reduced well, which is conducive to avoiding the same preset condition from participating in subsequent judgments repeatedly. The number of conditions after deduplication can be multiple.
[0046] S130. Obtain service data based on the conditions after deduplication, and determine whether the service data meets the conditions after deduplication to obtain a judgment result. Exemplarily, for the variables in the conditions after deduplication, obtain the data values in the service (i.e., service data) of these variables. Then, after determining the data values of the variables in the service, the data values can be matched with the conditions after deduplication to determine whether the data values meet the conditions after deduplication, so as to obtain a judgment result. Exemplarily, step S130 can be implemented through the alpha network in the phreak matching algorithm.
[0047] S140. Determine the target rule that the service data meets according to the judgment result. Since there is at least one preset condition in the target rule, and the conditions after deduplication are also the preset conditions in the target rule, therefore, determining whether the service data meets the conditions after deduplication is equivalent to determining whether the service data meets the preset conditions in the target rule. Furthermore, according to the judgment result, the target rule that the service data meets can be determined.
[0048] Exemplarily, in the case where the target rule that the service data meets cannot be determined, for example, there is no condition after deduplication that the service data meets in the judgment result, manual intervention can be prompted to ensure the continuous progress of the service and avoid delaying the service progress. Exemplarily, step S140 can be implemented through the beta network in the phreak matching algorithm.
[0049] S150. Execute the preset action corresponding to the target rule that the service data meets.
[0050] Exemplarily, if the number of target rules that the service data meets is multiple, or the preset actions corresponding to the target rules are multiple, the corresponding preset actions can be executed in the preset order successively to ensure the accurate progress of the service and meet the service requirements of users.
[0051] The service processing method of the present disclosure embodiment determines multiple target rules corresponding to the service scenario from multiple preset rules, and eliminates duplicates from the preset conditions in the multiple target rules, reducing the total number of preset conditions participating in subsequent judgments, which is beneficial to avoiding meaningless and duplicate preset conditions from participating in subsequent judgments, thereby improving the service processing efficiency. At the same time, service data is obtained based on the deduplicated conditions instead of directly obtaining the service data corresponding to all preset conditions, reducing the amount of service data obtained, which is beneficial to avoiding meaningless service data from participating in subsequent judgments, thereby improving the service processing efficiency. In addition, the deduplicated conditions make the judgment of service data more concise and clear, avoiding the complexity brought by redundant preset conditions, simplifying the service logic; determining the target rules satisfied by the service data based on the deduplicated conditions and executing the preset actions corresponding to the target rules can ensure the smooth progress of the service and meet the user's needs.
[0052] Regarding step S120, in some embodiments of the present disclosure, it may include steps S121 and S122 as Figure 3 shown.
[0053] S121. Group at least one preset condition of the multiple target rules based on the variables associated with the preset conditions, obtaining multiple groups of preset conditions, where the variables associated with the multiple groups of preset conditions are different from each other.
[0054] The variables associated with the preset conditions are the variables in the preset conditions. Since each preset condition includes variables, based on the variables in the preset conditions, the preset conditions in the multiple target rules can be accurately grouped.
[0055] Each group of obtained preset conditions may include at least one preset condition, and the preset conditions in each group of preset conditions may come from at least one target rule. For example, one preset condition in one target rule is "source = 1", and one preset condition in another target rule is "source = 2", then these two preset conditions can be divided into the same group. The types of variables in a group of preset conditions can be one or more. Since the preset conditions of the same type of variable will be divided into the same group, subsequent deduplication can be accurately completed in units of groups, improving the coverage rate and accuracy of deduplication.
[0056] S122. Remove the duplicate preset conditions in each of the multiple groups of preset conditions respectively, obtaining multiple groups of deduplicated conditions.
[0057] Exemplarily, for each set of preset conditions among multiple sets of preset conditions, one preset condition in the set can be compared with other preset conditions in the set in sequence. If there are other preset conditions that are the same as one preset condition in the set, the same other preset conditions are deleted, so as to achieve the purpose of deduplication. Since deduplication is performed in each group, the number of groups of conditions after deduplication is the same as the number of groups of preset conditions before deduplication.
[0058] The service processing method of the above embodiment groups multiple preset conditions to obtain multiple sets of preset conditions with mutually different variables, and then performs deduplication on each set of preset conditions respectively, improving the accuracy and efficiency of deduplication, reducing the total number of preset conditions participating in subsequent judgments, facilitating avoiding duplicate preset conditions from participating in subsequent judgments, thereby improving the service processing efficiency and being conducive to improving the performance and response speed of the system.
[0059] Regarding step S121, in some embodiments of the present disclosure, specifically, it may be: grouping at least one preset condition of multiple target rules in a way that one variable divides one group to obtain multiple sets of preset conditions.
[0060] The total number of types of variables existing in multiple target rules is the number of groups obtained after grouping.
[0061] The service processing method of the above embodiment ensures that there is exactly one variable in multiple preset conditions within each group in a way that one variable divides one group, making the grouping result clear and definite, facilitating subsequent deduplication operations. Moreover, through this simple grouping method, it is more convenient to manage and maintain the preset conditions within each group, reducing complexity and the possibility of errors.
[0062] Regarding step S130, in some embodiments of the present disclosure, the conditions after deduplication include multiple groups; correspondingly, "judging whether the service data meets the conditions after deduplication to obtain a judgment result" in step S130 may include steps S131 and S132 as Figure 4 shown.
[0063] S131. Determine the priorities of multiple sets of conditions after deduplication.
[0064] The priorities of multiple sets of conditions after deduplication can be pre-configured by relevant personnel or automatically generated by other algorithms, which are not limited herein.
[0065] S132. Based on the priorities, judge in sequence whether the service data meets multiple sets of conditions after deduplication to obtain a judgment result.
[0066] The priorities of multiple groups of deduplicated conditions can be different from each other. Therefore, each group of deduplicated conditions among multiple groups of deduplicated conditions can participate in the judgment of business data in sequence according to the priority order. The priorities of multiple groups of deduplicated conditions can also be partially the same, and multiple groups of deduplicated conditions with the same priority can simultaneously participate in the judgment of business data separately.
[0067] Exemplarily, regardless of whether the business data meets a group of deduplicated conditions with a high priority, it does not affect the subsequent judgment of whether the business data meets a group of deduplicated conditions with a low priority.
[0068] In the business processing method of the above embodiment, by introducing the priorities of multiple groups of deduplicated conditions, it is ensured that all multiple groups of deduplicated conditions can accurately and effectively participate in the judgment of business data, improving the rationality of decision-making and the accuracy of judgment results. At the same time, the priorities of each group of deduplicated conditions can be dynamically adjusted according to different business requirements, enabling the system to better adapt to different business needs and enhancing flexibility and adaptability.
[0069] Regarding step S131, in some embodiments of the present disclosure, the variables associated with multiple groups of deduplicated conditions are different from each other, and each group of deduplicated conditions is associated with one variable; correspondingly, step S131 may include steps S1311 and S1312 as Figure 5 shown.
[0070] S1311. Based on the mapping relationship between the preset priority and the preset variable, determine the priorities corresponding to the variables associated with multiple groups of deduplicated conditions.
[0071] The mapping relationship between the preset priority and the preset variable can be pre-configured by relevant personnel. By searching this mapping relationship, the priorities corresponding to the variables associated with each group of deduplicated conditions among multiple groups of deduplicated conditions can be accurately and quickly determined.
[0072] S1312. Use the priorities corresponding to the variables associated with multiple groups of deduplicated conditions as the priorities of multiple groups of deduplicated conditions.
[0073] In the business processing method of the above embodiment, based on the mapping relationship between the preset priority and the preset variable, the priorities corresponding to the variables associated with multiple groups of deduplicated conditions are automatically determined, and the priorities corresponding to the variables associated with multiple groups of deduplicated conditions are used as the priorities of multiple groups of deduplicated conditions, reducing manual intervention and improving the degree of automation. Since the variables associated with multiple groups of deduplicated conditions are different from each other, and each group of deduplicated conditions is only associated with one variable, therefore, directly using the priority of the variable as the priority of a group of deduplicated conditions corresponding to the variable has a more concise logic and is more convenient to configure. At the same time, if the business requirements change, the dynamic adjustment of the priority can be quickly achieved by adjusting the mapping relationship, making the system have good scalability and maintainability.
[0074] Regarding step S132, in some embodiments of the present disclosure, it may specifically include: for each set of deduplicated conditions among multiple sets of deduplicated conditions, add the deduplicated conditions in this set of deduplicated conditions that are satisfied by the data values of the variables associated with this set of deduplicated conditions to the judgment result.
[0075] Exemplarily, for a set of deduplicated conditions, if the data values of the variables associated with this set of deduplicated conditions satisfy a part of the deduplicated conditions in it, but do not satisfy the remaining part of the deduplicated conditions in it, then the satisfied part of the deduplicated conditions will be added to the judgment result, while the remaining part of the deduplicated conditions that are not satisfied will not be added to the judgment result, thereby simplifying the judgment result.
[0076] If the data values of the variables associated with a set of deduplicated conditions do not satisfy any of the deduplicated conditions in this set of deduplicated conditions, then none of the deduplicated conditions in this set of deduplicated conditions will be added to the judgment result.
[0077] If the data values of the variables associated with a set of deduplicated conditions satisfy each of the deduplicated conditions in this set of deduplicated conditions, then each of the deduplicated conditions in this set of deduplicated conditions will be added to the judgment result.
[0078] After the judgment of each set of deduplicated conditions among multiple sets of deduplicated conditions is completed, the judgment result can be determined.
[0079] The service processing method of the above embodiments adds the deduplicated conditions satisfied by the data values in each set of deduplicated conditions to the judgment result, so that the judgment result can include all the deduplicated conditions satisfied by the service data. Furthermore, through the judgment result, it can be accurately and clearly determined which deduplicated conditions are satisfied by the service data, thereby providing data support for determining the target rules satisfied by the service data.
[0080] Regarding step S132, in other embodiments, it may not add the deduplicated conditions satisfied by the data values to the judgment result, but add the identifiers of the deduplicated conditions satisfied by the data values to the judgment result, thereby simplifying the judgment result and facilitating storage.
[0081] Regarding step S140, in some embodiments of the present disclosure, the judgment result includes the deduplicated conditions satisfied by the service data; correspondingly, step S140 may include steps S141 and S142 as Figure 6 shown.
[0082] S141. Combine the deduplicated conditions satisfied by the service data to obtain multiple combined rules.
[0083] Exemplarily, multiple combined rules can be obtained by randomly permuting and combining multiple deduplicated conditions satisfied by the service data, or multiple combined rules can be obtained by directionally combining multiple deduplicated conditions satisfied by the service data according to the position order of the multiple deduplicated conditions satisfied by the service data in each target rule.
[0084] S142. Use the combined rule identical to the target rule as the target rule satisfied by the service data.
[0085] Exemplarily, in the case where there is no combined rule identical to the target rule, the target rule satisfied by the service data cannot be determined. At this time, manual intervention can be prompted to ensure the continuous progress of the service and avoid delaying the service progress.
[0086] In the service processing method of the above embodiment, by combining the deduplicated conditions satisfied by the service data, multiple combined rules are obtained, and the combined rule identical to the target rule is used as the target rule satisfied by the service data, ensuring that the determined target rule satisfied by the service data completely matches the service requirements and improving the accuracy of service processing. Since the number of deduplicated conditions satisfied by the service data is less than the number of preset conditions in the target rules corresponding to the service scenario, in this embodiment, instead of matching each preset condition in each target rule corresponding to the service scenario with the preset conditions in the judgment result one by one, the deduplicated conditions satisfied by the service data are combined to obtain combined rules and then the combined rules are matched with the target rules corresponding to the service scenario, thereby saving the matching efficiency and improving the service processing speed.
[0087] Regarding step S140, in other embodiments, each preset condition in each target rule can also be matched with the preset conditions in the judgment result one by one. Furthermore, if all the preset conditions in a target rule exist as the same deduplicated conditions in the judgment result, then this target rule can be used as a target rule satisfied by the service data.
[0088] Please refer to Figure 7 , in an example, the service processing method may include the following steps S201 to S209. The content related to steps S201 to S209 can refer to the description of the above embodiment. For the sake of brevity, it will not be repeated here.
[0089] In step S201, determine the service scenario.
[0090] In step S202, determine multiple target rules corresponding to the service scenario from multiple preset rules. For example Figure 8The first target rule, the second target rule, and the third target rule shown, where the first target rule is: City = 50100 & Source = 1 & Available housing > 1 & Customer type = 1 & Precise match Fact.func() = true, the second target rule is: City = 50200 & Source = 1 & Customer type = 1 & Precise match Fact.func() = true, and the third target rule is: City = 50200 & Source = 1 & Available housing > 1 & Precise match Fact.func() = true.
[0091] In step S203, in a way of dividing one group by one variable, at least one preset condition of multiple target rules is grouped to obtain multiple groups of preset conditions. As Figure 8 shown, the city group C1, the source group C2, the precise match group C3, the customer type group C4, and the available housing group C5.
[0092] In step S204, duplicate preset conditions in multiple groups of preset conditions are removed respectively to obtain multiple groups of deduplicated conditions. In Figure 8 the example, the deduplicated conditions of the city group C1 are City = 50100 and City = 50200, the deduplicated conditions of the source group C2 are Source = 1, the deduplicated conditions of the precise match group C3 are Fact.func() = true, the deduplicated conditions of the customer type group C4 are Customer type = 1, and the deduplicated conditions of the available housing group C5 are Available housing > 1.
[0093] In step S205, business data is obtained based on the deduplicated conditions. In Figure 8 the example, the data value of the available housing is queried by the electronic device from the business system through RPC (Remote Procedure Call) and returned by the business system.
[0094] In step S206, the priorities of multiple groups of deduplicated conditions are determined.
[0095] In step S207, based on the priorities, it is judged in turn whether the business data meets multiple groups of deduplicated conditions to obtain a judgment result. In Figure 8 the example, first it is judged whether the data value of the city in the business data meets (matches) the deduplicated conditions of the city group C1, then it is judged whether the data value of the source in the business data meets the deduplicated conditions of the source group C2, then it is judged whether the data value of the precise match in the business data meets the deduplicated conditions of the precise match group C3, then it is judged whether the data value of the customer type in the business data meets the deduplicated conditions of the customer type group C4, and finally it is judged whether the data value of the available housing in the business data meets the deduplicated conditions of the available housing group C5.
[0096] In step S208, determine the target rule(s) satisfied by the service data according to the judgment result. In Figure 8 the example of
[0097]
[0098] if all the preset conditions of the first target rule are satisfied by the service data, then the first target rule is the target rule satisfied by the service data, and the same applies to the second and third target rules. Based on any of the above embodiments, the present disclosure also provides a service processing apparatus.
[0099] Figure 9 is a schematic structural diagram of a service processing apparatus according to an embodiment of the present disclosure.
[0100] As Figure 9 shown, the service processing apparatus includes: A first determination module 110, configured to determine multiple target rules corresponding to a service scenario from multiple preset rules, where the multiple target rules respectively include at least one preset condition and a preset action; A deduplication module 120, configured to deduplicate at least one preset condition of the multiple target rules to obtain deduplicated conditions; An acquisition module 130, configured to acquire service data based on the deduplicated conditions; A judgment module 140, configured to judge whether the service data satisfies the deduplicated conditions to obtain a judgment result; A second determination module 150, configured to determine the target rule(s) satisfied by the service data according to the judgment result; An execution module 160, configured to execute the preset action corresponding to the target rule(s) satisfied by the service data.
[0101] The above service processing apparatus may be in the form of computer software, and each module of the above service processing apparatus may be implemented by computer software modules.
[0102] In some embodiments of the present disclosure, the deduplication module 120 is configured to: group at least one preset condition of the multiple target rules based on the variables associated with the preset conditions to obtain multiple groups of preset conditions, where the variables associated with the multiple groups of preset conditions are different from each other; and respectively remove the duplicate preset conditions in the multiple groups of preset conditions to obtain multiple groups of deduplicated conditions.
[0103] In some embodiments of the present disclosure, the deduplication module 120 is configured to: group at least one preset condition of the multiple target rules in a way that one variable divides one group to obtain multiple groups of preset conditions.
[0104] In some embodiments of the present disclosure, the deduplication conditions after deduplication include multiple groups; correspondingly, the determination module 140 is configured to: determine the priorities of the multiple groups of deduplication conditions after deduplication; and based on the priorities, sequentially determine whether the service data meets the multiple groups of deduplication conditions after deduplication to obtain a determination result.
[0105] In some embodiments of the present disclosure, the variables associated with the multiple groups of deduplication conditions after deduplication are different from each other, and each group of deduplication conditions after deduplication is associated with one variable; correspondingly, the determination module 140 is configured to: based on the mapping relationship between the preset priorities and the preset variables, determine the priorities corresponding to the variables associated with the multiple groups of deduplication conditions after deduplication; and use the priorities corresponding to the variables associated with the multiple groups of deduplication conditions after deduplication as the priorities of the multiple groups of deduplication conditions after deduplication.
[0106] In some embodiments of the present disclosure, the service data includes the data values of the variables associated with the multiple groups of deduplication conditions after deduplication; correspondingly, the determination module 140 is configured to: for each group of deduplication conditions after deduplication among the multiple groups of deduplication conditions after deduplication, add the deduplication conditions after deduplication in this group of deduplication conditions that are satisfied by the data values of the variables associated with this group of deduplication conditions after deduplication to the determination result.
[0107] In some embodiments of the present disclosure, the determination result includes the deduplication conditions satisfied by the service data; correspondingly, the second determination module 150 is configured to: combine the deduplication conditions satisfied by the service data to obtain multiple combination rules; and use the combination rules that are the same as the target rule as the target rule satisfied by the service data.
[0108] For the specific implementation process of the functions and roles of each module in the above device, please refer to the implementation process of the corresponding steps in the above method for details, which will not be elaborated here.
[0109] The execution subject of the service processing method in the specific embodiments of the present disclosure may be an electronic device such as a server, a mobile phone, or a computer.
[0110] Therefore, based on any one of the above embodiments, the present disclosure further provides an electronic device, and this electronic device can execute the service processing method of any one of the above embodiments described in the present disclosure.
[0111] Figure 10 It is a structural schematic diagram of an electronic device 1000 according to an embodiment of the present disclosure.
[0112] The hardware structure of the electronic device 1000 can be implemented using a bus architecture. The bus architecture can include any number of interconnected buses and bridges, depending on the specific application of the hardware and the overall design constraints. The bus 1100 connects various circuits including one or more processors 1200, a memory 1300, and / or hardware modules together. The bus 1100 can also connect various other circuits 1400 such as peripheral devices, voltage regulators, power management circuits, external antennas, etc.
[0113] The bus 1100 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Component (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, only one connection line is used in this figure, but it does not mean that there is only one bus or one type of bus.
[0114] The present disclosure also provides a readable storage medium in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the above-mentioned method. The "readable storage medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples of the readable storage medium include the following: an electrical connection part (electronic device) having one or more wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM), etc.
[0115] The present disclosure also provides a computer program product. The method of the present disclosure can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed, the process or function of the present disclosure is executed in whole or in part.
[0116] The computer program or instructions can be stored in a readable storage medium, or transmitted from one readable storage medium to another readable storage medium. For example, the computer program or instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The readable storage medium can be any available medium that can be accessed or a data storage device such as a server or data center integrating one or more available mediums. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it can also be an optical medium, such as a digital video disc; it can also be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or can include both volatile and non-volatile types of storage media.
[0117] Those skilled in the art should understand that the embodiments of the present disclosure may be provided as a method, a system, or a computer program product. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0118] The present disclosure is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the present disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of blocks.
[0119] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that realize the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of blocks.
[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of blocks.
[0121] In the description of this specification, the description with reference to terms such as "one embodiment / way", "some embodiments / ways", "example", "specific example", or "some examples" means that the specific features, structures, or characteristics described in connection with the embodiment / way or example are included in at least one embodiment / way or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment / way or example. Moreover, the specific features, structures, or characteristics described can be combined in a suitable manner in any one or more embodiments / ways or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments / ways or examples described in this specification and the features of different embodiments / ways or examples.
[0122] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.
[0123] Those skilled in the art should understand that the above embodiments are only for clearly explaining the present disclosure and not for limiting the scope of the present disclosure. For those skilled in the art, other changes or variations can be made on the basis of the above disclosure, and these changes or variations are still within the scope of the present disclosure.
Claims
1. A service processing method, characterized in that, including: determining multiple target rules corresponding to a business scenario from multiple preset rules, where each of the multiple target rules includes at least one preset condition and a preset action; deduplicating at least one preset condition of the multiple target rules to obtain deduplicated conditions; acquiring business data based on the deduplicated conditions, and determining whether the business data meets the deduplicated conditions to obtain a judgment result; determining the target rules met by the business data according to the judgment result; and executing the preset actions corresponding to the target rules met by the business data.
2. The service processing method according to claim 1, characterized in that Deduplicating at least one preset condition of the multiple target rules to obtain deduplicated conditions, including: grouping at least one preset condition of the multiple target rules based on the variables associated with the preset conditions to obtain multiple groups of preset conditions, where the variables associated with the multiple groups of preset conditions are different from each other; and respectively removing the duplicate preset conditions in the multiple groups of preset conditions to obtain multiple groups of the deduplicated conditions.
3. The service processing method according to claim 2, characterized in that, Grouping at least one preset condition of the multiple target rules based on the variables associated with the preset conditions to obtain multiple groups of preset conditions, including: grouping at least one preset condition of the multiple target rules in a way that one variable divides one group to obtain the multiple groups of preset conditions.
4. The service processing method according to claim 1, wherein The deduplicated conditions include multiple groups; Determining whether the business data meets the deduplicated conditions to obtain a judgment result, including: determining the priorities of the multiple groups of deduplicated conditions; and based on the priorities, sequentially determining whether the business data meets the multiple groups of deduplicated conditions to obtain the judgment result.
5. The service processing method according to claim 4, characterized in that The variables associated with the multiple groups of deduplicated conditions are different from each other, and each group of deduplicated conditions is associated with one variable; Determining the priorities of the multiple groups of deduplicated conditions, including: determining the priorities corresponding to the variables associated with the multiple groups of deduplicated conditions based on the mapping relationship between preset priorities and preset variables; and taking the priorities corresponding to the variables associated with the multiple groups of deduplicated conditions as the priorities of the multiple groups of deduplicated conditions.
6. The service processing method according to claim 4, wherein The business data includes data values of the variables associated with the multiple groups of deduplicated conditions; Based on the priorities, sequentially determining whether the business data meets the multiple groups of deduplicated conditions to obtain the judgment result, including: for each group of deduplicated conditions in the multiple groups of deduplicated conditions, adding the deduplicated conditions in the group of deduplicated conditions that the data value of the variable associated with the group of deduplicated conditions meets to the judgment result.
7. The service processing method according to claim 1, wherein The judgment result includes the deduplicated conditions met by the business data; Determining the target rules met by the business data according to the judgment result, including: combining the deduplicated conditions met by the business data to obtain multiple combined rules; and taking the combined rules that are the same as the target rules as the target rules met by the business data.
8. An electronic device, characterized in that, including: a memory that stores execution instructions; and a processor that executes the execution instructions stored in the memory, so that the processor executes the business processing method according to any one of claims 1 to 7.
9. A readable storage medium, characterized in that, The readable storage medium stores execution instructions, and when the execution instructions are executed by a processor, they are used to implement the service processing method described in any one of claims 1 to 7.
10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the service processing method described in any one of claims 1 to 7.