Data rule management method and system, electronic equipment and medium
By decomposing and combining rules into a set of normalized atomic items and performing coverage and conflict detection, the high cost and high error rate caused by inconsistent granularity in existing business rule management solutions are solved, achieving rule consistency and traceability and reducing release risks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-04-07
AI Technical Summary
In existing business rule management solutions, inconsistent business configuration granularity leads to high editing costs and error rates. Furthermore, there is insufficient static detection and repair of issues such as interval continuity, overlap, and gaps, resulting in high release risks.
By acquiring user operation information, the forward decomposition of the combination rules is broken down into a set of normalized atomic items, and coverage and conflict detection are performed. The atomic item change set is generated and stored in the database. The reverse parsing is used to form the target combination rule, which supports a two-way editing mechanism, including visual repair and transactional synchronization.
Ensure consistency between combination rules and atomic item semantics, reduce release risks and error rates, improve traceability, and reduce editing and review costs.
Smart Images
Figure CN121809456A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data rule management technology, and in particular to a data rule management method, system, electronic device, and medium. Background Technology
[0002] To improve online matching performance, existing systems generally store business rules atomically; however, business configuration preferences are batch-operated using combined rules (aggregating entries based on business semantic dimensions). This inconsistency in granularity leads to high editing costs and error rates. Existing business rule management solutions are mostly unidirectional conversion and distribution, and lack sufficient static detection and repair for issues such as interval continuity, overlap, and gaps, resulting in high release risks. Summary of the Invention
[0003] In view of this, the purpose of the present invention is to provide a data rule management method, system, electronic device and medium to ensure the consistency and traceability of data rules in the process of editing, storing and distributing.
[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a data rule management method, comprising: acquiring user operation information on rule dimensions through a visual editing interface to obtain initial combination rules; performing forward decomposition of the initial combination rules to obtain a set of normalized atomic items; performing coverage and conflict detection on the set of normalized atomic items to obtain detection results; if the detection results are normal, generating an atomic item change set based on the detection results, storing the atomic item change set in an atomic item database, and performing reverse parsing based on the atomic items in the atomic item database to obtain the target combination rule.
[0005] Optionally, after performing coverage and conflict detection on the normalized atomic item set and obtaining the detection results, the method further includes: if the detection result is abnormal, displaying the abnormal detection result through the visual editing interface, and responding to the user's triggering operation of the repair button in the visual editing interface to repair the initial combination rule.
[0006] Optionally, the initial combination rules are decomposed in a forward manner to obtain a normalized set of atomic items, including: based on a preset atomic template and normalization rules, the initial combination rules are decomposed in a forward manner to obtain a set of atomic items; wherein, the normalization rules include at least: fixed-order sorting of dimension keys, half-open intervals as interval endpoints, operator standardization and value range deduplication; the atomic item set is sorted, deduplicated and equivalently merged according to the dimension keys to obtain a normalized set of atomic items.
[0007] Optionally, the atomic item change set is stored in the atomic item database, including: persistently storing the atomic item change set in the atomic item database using a transactional approach; wherein the atomic item change set includes: addition, deletion and update operations of atomic items; and incrementally synchronizing the atomic item change set to the rule engine through an event stream or message queue.
[0008] Optionally, reverse parsing is performed based on atomic items in the atomic item database to obtain the target combination rule, including: grouping and aggregating atomic items according to the rule dimension, and merging atomic items based on interval continuity to obtain the target combination rule.
[0009] Optionally, the method further includes: performing coverage detection on the normalized set of atomic items based on a pre-defined priority matrix.
[0010] Optionally, the method further includes: performing a pre-release simulation of the target combination rules to obtain the hit results and impact range of the target combination rules.
[0011] Secondly, the present invention provides a data rule management system, comprising: a visual editing module for acquiring user operation information on rule dimensions through a visual editing interface to obtain initial combination rules; a rule parsing module for forward decomposing the initial combination rules to obtain a set of normalized atomic items; a conflict and coverage detection module for performing coverage and conflict detection on the set of normalized atomic items to obtain detection results; and a reverse parsing module for generating an atomic item change set based on the detection results if the detection results are normal, storing the atomic item change set in an atomic item database, and performing reverse parsing based on the atomic items in the atomic item database to obtain the target combination rule.
[0012] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the steps of the method provided in any of the first aspects above.
[0013] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, performs the steps of the method provided in any of the first aspects above.
[0014] This invention brings the following beneficial effects: The data rule management method, system, electronic device, and medium provided by this invention first acquire user operation information on rule dimensions through a visual editing interface to obtain initial combination rules; then, the initial combination rules are forward decomposed to obtain a set of normalized atomic items; next, the normalized atomic item set is subjected to coverage and conflict detection to obtain detection results; if the detection results are normal, an atomic item change set is generated based on the detection results and stored in an atomic item database; and the atomic items in the atomic item database are reverse-parsed to obtain the target combination rule. This method provides a bidirectional editable mechanism for combination rules. By forward decomposing the initial combination rules into a set of normalized atomic items and reverse-parsening the atomic items in the atomic item database to form combination rules, the consistency between the combination rules and the semantics of the atomic items can be ensured. By performing coverage and conflict detection on the set of normalized atomic items and storing the atomic item change set in the atomic item database, the risk of release and error rate can be reduced, while ensuring the traceability of the rules.
[0015] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.
[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0018] Figure 1 A flowchart illustrating a data rule management method provided in an embodiment of the present invention; Figure 2 A schematic diagram of a visual editing interface provided in an embodiment of the present invention; Figure 3 A flowchart illustrating another data rule management method provided in an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a data rule management system provided in an embodiment of the present invention; Figure 5 An architecture diagram of a data rule management system provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0020] Current business rule management solutions are mostly one-way conversion and distribution, and lack static detection and repair of issues such as interval continuity, overlap and gaps, resulting in high release risks.
[0021] Based on this, the data rule management method, system, electronic device and medium provided in the embodiments of the present invention can ensure the consistency and traceability of data rules in the process of editing, storing and issuing.
[0022] To facilitate understanding of this embodiment, a data rule management method disclosed in this invention will first be described in detail. This method can be executed by electronic devices, such as smartphones, computers, and tablets. See also Figure 1 The flowchart shown is a data rule management method, which mainly includes the following steps S101 to S104: Step S101: Obtain the user's operation information on the rule dimensions through the visual editing interface to obtain the initial combination rules.
[0023] In one implementation, see Figure 2 The diagram illustrates a visual editing interface that supports batch multi-selection, conditional filtering, and single-scene coverage, presenting coverage differences in a comparison view. Users can add, modify, or delete combination rules through conditional filtering and dimension multi-selection in the visual editing interface to obtain the initial combination rules.
[0024] Step S102: Decompose the initial combination rules in the forward direction to obtain the normalized set of atomic terms.
[0025] In one implementation, firstly, based on a preset atomic template and normalization rules, the initial combination rules are decomposed in a forward manner to obtain a set of atomic items; then, the set of atomic items is sorted, deduplicated, and equivalently merged according to the dimension key to obtain a normalized set of atomic items.
[0026] The preset atomic templates are the types of pre-configured atomic items, such as departure city, destination city, vehicle type, time period, etc. The normalization rules include at least: fixed order sorting of dimension keys (i.e., sorting the atomic items according to the fixed order of the dimension keys of the pre-set rule dimensions), half-open intervals for interval endpoints (i.e., for interval dimensions (e.g., time, amount, etc.), the interval endpoints are all half-open intervals, such as left-closed and right-open [start,end)), operator standardization (i.e., unifying the operators according to the preset standards), and value range deduplication (i.e., deduplicating the same value range).
[0027] In this embodiment of the invention, based on preset atomic templates and normalization rules, the initial combination rules are forward decomposed into a set of atomic items, and the atomic items are sorted by dimension key, deduplicated, and equivalently merged to form a normalized set of atomic items. The rule expressions can also be normalized into a sorted abstract syntax tree or conjunctive normal form to optimize comparison and merging.
[0028] Step S103: Perform coverage and conflict detection on the normalized atomic item set to obtain the detection results.
[0029] In one implementation, coverage and conflict detection are performed on the normalized set of atomic items. Coverage and conflict detection are implemented based on interval merging and difference calculation. The detection includes at least: interval continuity detection, interval overlap detection, interval hole detection, and out-of-bounds and zero-length detection. The interval continuity detection supports endpoint tolerance and half-open interval model configuration.
[0030] Step S104: If the detection result is normal, generate an atomic item change set based on the detection result, store the atomic item change set in the atomic item database, and perform reverse parsing based on the atomic items in the atomic item database to obtain the target combination rule.
[0031] In one implementation, if the detection result is normal (i.e. the normalized atomic item set passes the detection), an atomic item change set (i.e., the minimum change set for atomic items) is generated based on the detection result, and the atomic item change set is stored in the atomic item database. Based on the reverse parsing rules of equivalence guarantee, the combination rules (i.e. the target combination rules) are reconstructed from the atomic item database, and the reconstructed target combination rules are displayed back to the visual editing interface.
[0032] In practical implementation, when reconstructing the combination rules, atomic items can be grouped and aggregated according to the rule dimension, and segments can be merged based on interval continuity to obtain the target combination rules. In this embodiment of the invention, the rules obtained by sequentially performing forward and inverse transformations on the same normalized set of atomic items are semantically equivalent.
[0033] The data rule management method provided in this embodiment of the invention offers a bidirectional editable mechanism for combined rules. By forward decomposing the initial combined rule into a set of normalized atomic items and reverse parsing the atomic items in the atomic item database to form combined rules, the consistency between the combined rules and the semantics of the atomic items can be ensured. By performing coverage and conflict detection on the set of normalized atomic items and storing the atomic item change set in the atomic item database, the risk of release and error rate can be reduced, while ensuring the traceability of the rules.
[0034] In one implementation, after performing coverage and conflict detection on the normalized atomic item set and obtaining the detection results, the method further includes: if the detection result is abnormal, displaying the abnormal detection result through a visual editing interface, and repairing the initial combination rules in response to the user's triggering operation of the repair button in the visual editing interface.
[0035] In practice, if the detection results of the normalized atomic item set are abnormal (e.g., overlapping intervals, out-of-bounds errors, etc.), the abnormal detection results will be displayed through a visual editing interface. See also Figure 2 As shown, the visual editing interface provides conflict highlighting and one-click repair. It can highlight the abnormal detection results and users can use the repair button to repair abnormalities in the initial combination rules, such as: merging overlapping intervals (overlapping abnormality), automatically filling missing intervals (hole abnormality), forcibly correcting to the boundary value (out-of-bounds abnormality), deleting or prompting the user to modify (zero length abnormality), etc.
[0036] To ensure the ordered consistency and at least-once delivery semantics of atomic items and combination rules, in this embodiment of the invention, when storing atomic item change sets in the atomic item database, the following methods, including but not limited to, can be used: First, the atomic item change sets are persistently stored in the atomic item database using a transactional approach; wherein, the atomic item change sets include: addition, deletion, and update operations of atomic items, and have idempotent keys; then, the atomic item change sets are incrementally synchronized to the rule engine through event streams or message queues. The storage of atomic items establishes a dimensional inverted index to accelerate aggregation and reverse parsing.
[0037] In one implementation, the method further includes: performing coverage detection on the normalized set of atomic items based on a pre-defined priority matrix. Specifically, when performing coverage and conflict detection, a matching decision is determined based on the scene coverage priority matrix (i.e., determining whether to perform interval coverage based on the priority of the atomic items), wherein the priority includes at least one of: most specific priority, explicit coverage priority, or latest release priority.
[0038] In one implementation, the method further includes: performing a pre-release simulation on the target combination rule to obtain the hit results and impact range of the target combination rule. Specifically, to reduce release risk and error rate, before releasing the combination rule, a pre-release simulation can be performed to output a comparison of the hit results and impact range statistics of the target combination rule (i.e., the impact of adding, deleting, or updating the combination rule on other combination rules is obtained through pre-simulation), and a decision is made on whether to release the generated combination rule based on the simulation results.
[0039] Furthermore, the above method also supports version management and rollback, and performs overwrite and conflict detection and equivalence verification during rollback; concurrency control adopts row-level optimistic locking or vector clocking to lock the user when editing the combination rules to avoid concurrent editing conflicts.
[0040] The methods provided in this invention can be applied to the following scenarios: ride-sharing pricing rules: multi-dimensional matching of "city + vehicle type + time period + number of people + scenario + distance range"; risk control rules: configuration based on region, time, user group, event type, etc.; e-commerce promotion rules: combined configuration based on category, time window, customer group, etc. For ease of understanding, the above methods will be described in detail using ride-sharing pricing rules as an example. See [link / reference]. Figure 3 The flowchart shown first performs forward parsing on the combination rules to obtain a set of atomic items, and then performs normalization processing on the set of atomic items, including sorting, deduplication, merging, etc.
[0041] Specifically, this invention breaks down business rules into atomic items. These atomic items are represented using the following JSON structure: { "start_city":"Beijing", "end_city":"Shanghai", "car_type":"Economy type", "weekday":1, "time_slot":"06:00-12:00", "distance_range":"0-50", "passenger_number":2, "scene":"carpooling", "operator":"=", "version":"v1.0", "priority":"specific_first" } The set of atomic terms includes: Departure city and destination city: such as "Beijing" and "Shanghai"; Vehicle types: Economy and Luxury; Day of the week: 1~7 (0 indicates general rule); Time slots: 00:00-06:00, 06:00-12:00, 12:00-18:00, 18:00-24:00; Distance ranges: 0-10km, 10-30km, 30-50km, 50-100km, 100-600km; Passenger count: 1~4; Scenario: Carpooling, enjoying alone.
[0042] Then, the normalized set of atomic items is covered and conflict detected, including interval continuity, overlap, holes, out-of-bounds, zero length, etc.
[0043] Specifically, each interval is sorted according to its starting point. Boundary detection checks whether the upper and lower boundaries of the interval exceed a preset range; zero length detection checks whether the interval length is zero, which can be determined by whether the interval starting point is greater than or equal to the interval ending point; overlap detection checks whether two adjacent intervals overlap, which can be determined by whether the ending point of the previous interval is greater than the starting point of the next interval; and hole detection checks whether there is a gap between two adjacent intervals, which can be determined by whether the ending point of the previous interval is less than the starting point of the next interval.
[0044] If the test fails, a conflict / void message will be displayed in the visual editing interface, and a repair button will be provided.
[0045] Specifically, if {distance_range=0-30} and {distance_range=20-50} already exist, the system will detect them as overlapping ranges and highlight the conflict on the interface. If {distance_range=0-30} and {distance_range=40-50} already exist, the system will detect them as empty intervals [30-40] and the interface will prompt "One-click completion".
[0046] The repair strategies include: merging overlapping intervals into {min_start, max_end}; automatically filling missing intervals in empty intervals and prompting the user for confirmation; forcibly correcting out-of-bounds intervals to the boundary value; and deleting or prompting the user to modify zero-length intervals.
[0047] If the detection passes, a minimum change set is generated and stored in the atomic item database in a transactional manner. At the same time, the change set is incrementally synchronized to the rule engine, and the atomic items are reverse-analyzed to generate combined rules, which are then displayed back to the visual editing interface.
[0048] Specifically, here's an example of a combination rule: [Beijing to Shanghai, Economy, Monday, 06:00-12:00, 0-50km, 2 people, Carpooling] Corresponding set of atomic terms: {start_city=Beijing,end_city=Shanghai} {car_type=Economy} {weekday=1} {time_slot=06:00-12:00} {distance_range=0-50} {passenger_number=2} {scene=carpooling}.
[0049] During reverse analysis, the system aggregates atomic items by dimension and combines them into segments based on interval continuity, displaying the combination rules in the visualization interface.
[0050] The method provided in this invention can forward decompose combination rules into a set of normalized atomic items and reverse parse atomic items to form combination rules. Through equivalent round-trip transformations (normalization / sorting / redundancy removal), it ensures consistency between combination rules and atomic item semantics. Through coverage and conflict detection (continuity, overlap, holes, out-of-bounds, zero length) and one-click repair, it reduces the mismatch rate of combination rules. Through transactional persistence and incremental synchronization of the minimum change set, it reduces the release risk of combination rules. Through priority matrices and simulation / auditing / rollback, it improves differentiated configuration and traceability. It reduces the operational complexity from atomic item level O(n) to combination rule level O(m) (where m is the number of aggregated entries, typically m...). n), reducing editing and review costs.
[0051] In addition to the data rule management method provided in the foregoing embodiments, this invention also provides a data rule management system, see [link to previous embodiment]. Figure 4 The diagram shown illustrates the structure of a data rule management system, indicating that the system mainly comprises the following components: The visual editing module 401 is used to obtain the user's operation information on the rule dimensions through the visual editing interface, and to obtain the initial combination rules.
[0052] The rule parsing module 402 is used to perform forward decomposition of the initial combination rules to obtain a set of normalized atomic terms.
[0053] The conflict and coverage detection module 403 is used to perform coverage and conflict detection on the normalized set of atomic items and obtain the detection results.
[0054] The reverse parsing module 404 is used to generate an atomic item change set based on the detection result if the detection result is normal, store the atomic item change set in the atomic item database, and perform reverse parsing based on the atomic items in the atomic item database to obtain the target combination rule.
[0055] The data rule management system provided in this embodiment of the invention offers a bidirectional editable mechanism for combined rules. By forward decomposing the initial combined rules into a set of normalized atomic items and reverse parsing the atomic items in the atomic item database to form combined rules, the consistency between the combined rules and the semantics of the atomic items can be ensured. By performing coverage and conflict detection on the set of normalized atomic items and storing the atomic item change set in the atomic item database, the risk of release and error rate can be reduced, while ensuring the traceability of the rules.
[0056] In one embodiment, the system further includes a repair module, configured to: if the detection result is abnormal, display the abnormal detection result through a visual editing interface, and repair the initial combination rules in response to the user's triggering operation of the repair button in the visual editing interface.
[0057] In one implementation, the rule parsing module 402 is specifically used to: based on a preset atomic template and normalization rules, perform forward decomposition of the initial combination rules to obtain a set of atomic items; wherein, the normalization rules include at least: fixed-order sorting of dimension keys, half-open intervals as interval endpoints, operator standardization, and deduplication of value range; sort, deduplicate, and merge the set of atomic items according to the dimension keys to obtain a set of normalized atomic items.
[0058] In one implementation, the reverse parsing module 404 is specifically used to: persistently store the atomic item change set in the atomic item database using a transaction method; wherein the atomic item change set includes: addition operation, deletion operation and update operation of atomic items; and incrementally synchronize the atomic item change set to the rule engine through event stream or message queue.
[0059] In one implementation, the reverse parsing module 404 is specifically used to: group and aggregate atomic items according to the rule dimension, and merge atomic items based on interval continuity to obtain the target combination rule.
[0060] In one embodiment, the system further includes a priority coverage detection module, used to perform coverage detection on the normalized set of atomic items based on a pre-set priority matrix.
[0061] In one embodiment, the system further includes a pre-simulation module for pre-releasing simulation of the target combination rules to obtain the hit results and impact range of the target combination rules.
[0062] This invention also provides an architecture diagram of another data rule management system, see [link / reference]. Figure 5 As shown, it mainly includes: a visual editing module that provides interface interaction, difference highlighting, and repair operations; a rule parsing module responsible for atomic decomposition; a reverse parsing module responsible for restoring combined rules from atomic items; a normalization processor responsible for normalizing atomic items; a conflict and coverage detection module that performs continuity, overlap, and hole detection; a data synchronization module responsible for synchronizing atomic items to the atomic item database and rule engine; and a version and rollback module that supports historical version management, auditing, and rollback.
[0063] It should be noted that the system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned method embodiment. The specific numerical values provided in the implementation of this invention are merely exemplary and are not intended to limit the scope of the invention.
[0064] This invention also provides an electronic device, specifically, the electronic device includes a processor and a storage device; the storage device stores a computer program, and the computer program, when run by the processor, executes the method described in any of the above embodiments.
[0065] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 100 includes: a processor 60, a memory 61, a bus 62, and a communication interface 63. The processor 60, the communication interface 63, and the memory 61 are connected through the bus 62. The processor 60 is used to execute executable modules, such as computer programs, stored in the memory 61.
[0066] The memory 61 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 63 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.
[0067] Bus 62 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.
[0068] The memory 61 is used to store programs. After receiving an execution instruction, the processor 60 executes the program. The method executed by the device for defining the flow process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 60 or implemented by the processor 60.
[0069] Processor 60 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 60 or by instructions in software form. Processor 60 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 61. Processor 60 reads the information in memory 61 and, in conjunction with its hardware, completes the steps of the above method.
[0070] The computer program product of the readable storage medium provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be repeated here.
[0071] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0072] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A data rule management method, characterized in that, include: Obtain user operation information on rule dimensions through the visual editing interface to obtain the initial combination rules; The initial combination rules are decomposed in a forward manner to obtain a set of normalized atomic terms; The normalized set of atomic items is subjected to coverage and conflict detection to obtain the detection results; If the detection result is normal, an atomic item change set is generated based on the detection result, and the atomic item change set is stored in the atomic item database. The target combination rule is obtained by reverse parsing based on the atomic items in the atomic item database.
2. The method according to claim 1, characterized in that, After performing coverage and conflict detection on the normalized set of atomic items and obtaining the detection results, the method further includes: If the detection result is abnormal, the abnormal detection result will be displayed through the visual editing interface, and the initial combination rule will be repaired in response to the user's triggering operation of the repair button in the visual editing interface.
3. The method according to claim 1, characterized in that, The initial combination rule is decomposed in a forward manner to obtain a normalized set of atomic terms, including: Based on the preset atomic template and normalization rules, the initial combination rules are decomposed in a forward manner to obtain a set of atomic items; wherein, the normalization rules include at least: fixed-order sorting of dimension keys, half-open intervals as interval endpoints, operator standardization, and value range deduplication; The atomic item set is sorted, deduplicated, and equivalently merged according to the dimension key to obtain the normalized atomic item set.
4. The method according to claim 1, characterized in that, Storing the atomic item change set to the atomic item database includes: The atomic item change set is persistently stored in the atomic item database using a transaction approach; wherein, the atomic item change set includes: addition operations, deletion operations, and update operations of atomic items; The atomic item change set is incrementally synchronized to the rule engine via event stream or message queue.
5. The method according to claim 1, characterized in that, Reverse parsing is performed based on the atomic items in the atomic item database to obtain the target combination rules, including: The atomic items are grouped and aggregated according to the stated rule dimensions, and the atomic items are merged based on interval continuity to obtain the target combination rule.
6. The method according to claim 1, characterized in that, Also includes: Coverage detection is performed on the normalized set of atomic items based on a pre-defined priority matrix.
7. The method according to claim 1, characterized in that, Also includes: A pre-release simulation is performed on the target combination rule to obtain the hit result and the scope of influence of the target combination rule.
8. A data rule management system, characterized in that, include: The visual editing module is used to obtain the user's operation information on the rule dimensions through the visual editing interface, and to obtain the initial combination rules; The rule parsing module is used to perform forward decomposition of the initial combination rules to obtain a set of normalized atomic terms; The conflict and coverage detection module is used to perform coverage and conflict detection on the normalized set of atomic items and obtain the detection results. The reverse parsing module is used to generate an atomic item change set based on the detection result if the detection result is normal, store the atomic item change set in the atomic item database, and perform reverse parsing based on the atomic items in the atomic item database to obtain the target combination rule.
9. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program thereon, characterized in that, The computer program is executed by the processor to perform the steps of the method described in any one of claims 1 to 7.