Information generation method, information generation device, electronic device, and storage medium

Abstract

The present disclosure provides an information generation method, which can be applied to the field of artificial intelligence technology. The information generation method comprises: screening, according to a first target label, first unit information corresponding to the first target label from a pre-constructed information library to obtain M first unit information, wherein M is an integer greater than or equal to 2; and combining the M first unit information according to an association relationship between the M first unit information to generate target information; wherein the pre-constructed information library comprises N first information groups, the first information group comprises the first unit information, the first target label corresponding to the first unit information and the association relationship between the first unit information and a first other unit information, the first unit information is obtained by minimizing and disassembling first initial information, and N is an integer greater than or equal to M. The present disclosure also provides an information generation device, equipment, storage medium and program product.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, specifically to an information generation method, an information generation device, an electronic device, a storage medium, and a program product. Background Technology

[0002] With the continuous development of society, all walks of life are constantly generating various kinds of information. When using computer network systems to manage information, the information is directly stored through information databases.

[0003] In the process of implementing this disclosure, it was found that although storing information in an information database makes it convenient to directly access it, it also presents problems such as difficulty in intelligently configuring the information in the database and low efficiency in information configuration. Summary of the Invention

[0004] In view of the above problems, this disclosure provides an information generation method, an information generation apparatus, an electronic device, a storage medium, and a program product.

[0005] According to a first aspect of this disclosure, an information generation method is provided, comprising:

[0006] Based on the first target label, first unit information corresponding to the first target label is filtered from a pre-built information database to obtain M first unit information items, where M is an integer greater than or equal to 2; and

[0007] Based on the relationships between the M pieces of information in the first unit, the M pieces of information in the first unit are combined to generate the target information;

[0008] The pre-constructed information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the first initial information. N is an integer greater than or equal to M.

[0009] According to embodiments of this disclosure, it further includes:

[0010] Given that the second initial information has been obtained, T second information groups are obtained based on the second initial information. Each second information group includes second unit information, a second target label corresponding to the second unit information, and the association relationship between the second unit information and other second unit information, where T is an integer greater than or equal to 1; and

[0011] If, based on N first information groups, there are discrepancies among T second information groups, the information database is updated according to the discrepancies.

[0012] According to embodiments of this disclosure, it further includes:

[0013] For the second information group among the T second information groups, if it is determined that there is no first information group among the N first information groups that matches the second information group, the second information group is determined as the difference information group.

[0014] According to embodiments of this disclosure, when it is determined from N first information groups that there are differing information groups among T second information groups, updating the information database based on the differing information groups includes:

[0015] If, based on N first information groups, there are discrepancy information groups among T second information groups, then the difference level is obtained based on the discrepancy information groups.

[0016] Invoke the update strategy corresponding to the difference level; and

[0017] Based on the update strategy, the information database is updated according to the difference information groups.

[0018] According to embodiments of this disclosure, the difference levels include a first difference level and a second difference level;

[0019] Among these, updating the information database based on the update strategy and according to the difference information groups includes:

[0020] When the difference level is the first difference level.

[0021] The information database is updated based on the differences in information groups;

[0022] When the difference level is the second difference level.

[0023] Send an update request to a third party so that the third party can determine the appropriate action based on the update request; and

[0024] In response to receiving an operation method from a third party, the information database is updated based on the operation method and the difference information group.

[0025] According to embodiments of this disclosure, it further includes:

[0026] The information in the first unit is parsed to obtain the parsing results;

[0027] Based on the analysis results, determine the initial label corresponding to the information in the first unit;

[0028] Based on the category represented by the initial label, determine the target label corresponding to the initial label; and

[0029] Replace the initial label corresponding to the information in the first unit with the target label corresponding to the initial label.

[0030] According to embodiments of this disclosure, it further includes:

[0031] Based on the initial label, determine the association between the information in the first unit and the information in the first other units;

[0032] Based on the first unit information, the target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information, a first information group is obtained; and

[0033] Store the first information group in the information database.

[0034] According to embodiments of this disclosure, the first initial information includes policy information.

[0035] A second aspect of this disclosure provides an information generation apparatus, comprising:

[0036] The filtering module is used to filter first unit information corresponding to the first target label from a pre-built information database, obtaining M first unit information items, where M is an integer greater than or equal to 2; and

[0037] The combination module is used to combine the M pieces of information in the first unit according to the relationship between them, and generate the target information.

[0038] The pre-constructed information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the first initial information. N is an integer greater than or equal to M.

[0039] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the information generation method described above.

[0040] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the above-described information generation method.

[0041] The fifth aspect of this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described information generation method.

[0042] According to embodiments of this disclosure, by breaking down the information into its smallest units to obtain the first unit information, the problems of information redundancy or unreasonable information after configuration are avoided. Furthermore, according to multi-dimensional information groups, the first unit information, the first target tag corresponding to the first unit information, and the association relationships between the first unit information and other first unit information are stored in an information database. This facilitates the selection of first unit information from the database and the generation of target information, achieving intelligent information configuration that is convenient, fast, and improves information configuration efficiency. Attached Figure Description

[0043] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0044] Figure 1 This illustration schematically depicts application scenarios of an information generation method, information generation apparatus, electronic device, storage medium, and program product according to embodiments of the present disclosure.

[0045] Figure 2 A flowchart illustrating an information generation method according to an embodiment of the present disclosure is shown schematically;

[0046] Figure 3 A flowchart illustrating an information generation method according to another embodiment of this disclosure is shown schematically;

[0047] Figure 4 This illustration schematically shows an interactive flowchart of intelligent information configuration according to an embodiment of the present disclosure;

[0048] Figure 5 This illustration schematically shows an architecture diagram of a business rules information system according to an embodiment of the present disclosure;

[0049] Figure 6 This illustration schematically shows a diagram of the internal technical architecture of a business rules information system according to an embodiment of the present disclosure;

[0050] Figure 7 A schematic block diagram of an information generation apparatus according to an embodiment of the present disclosure is shown; and

[0051] Figure 8 A block diagram schematically illustrates an electronic device suitable for implementing an information generation method according to an embodiment of the present disclosure. Detailed Implementation

[0052] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0053] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0054] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0055] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0056] In the technical solution disclosed herein, the acquisition, storage, and application of user personal information comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and there is no violation of public order and good morals.

[0057] In the technical solutions of this disclosure, user authorization or consent is obtained before acquiring or collecting user personal information.

[0058] In related technologies, information databases store information generated through various business operations. This information is unprocessed and can be directly retrieved from the database when needed. However, if configuration of information in the database is required, direct retrieval can lead to information redundancy or unreasonable configurations, necessitating manual adjustments and processing. This consumes significant human and material resources and is inefficient.

[0059] For example, a business rules information system stores business rules information in a database at once. However, when managing this information, the system faces difficulties in intelligently configuring the rules, thus hindering the improvement of its intelligent management standards.

[0060] The embodiments of this disclosure provide an information generation method, including: filtering first unit information corresponding to the first target label from a pre-constructed information database according to a first target label to obtain M first unit information, where M is an integer greater than or equal to 2; and combining the M first unit information according to the association relationship between them to generate target information; wherein the pre-constructed information database includes N first information groups, each first information group including first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and first other unit information, the first unit information being obtained by minimizing the decomposition of first initial information, and N being an integer greater than or equal to M.

[0061] Figure 1 The illustrations depict application scenarios of information generation methods, information generation apparatuses, electronic devices, storage media, and program products according to embodiments of the present disclosure.

[0062] like Figure 1 As shown, application scenario 100 according to this embodiment may include terminal devices 101, 102, and 103, network 104, and server 105. Network 104 is used as a medium to provide a communication link between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0063] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0064] Terminal devices 101, 102, and 103 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0065] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using terminal devices 101, 102, and 103 (for example only). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0066] It should be noted that the information generation method provided in this disclosure embodiment can generally be executed by server 105. Correspondingly, the information generation apparatus provided in this disclosure embodiment can generally be located in server 105. The information generation method provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Correspondingly, the information generation apparatus provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105.

[0067] The information generation method provided in this embodiment can also be executed by terminal devices 101, 102, and 103. Correspondingly, the information generation apparatus provided in this embodiment can generally also be disposed in terminal devices 101, 102, and 103. The information generation method provided in this embodiment can also be executed by terminals other than terminal devices 101, 102, and 103. Correspondingly, the information generation apparatus provided in this embodiment can also be disposed in terminals other than terminal devices 101, 102, and 103.

[0068] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0069] The following will be based on Figure 1 The described scene, through Figures 2-6 The information generation method of the disclosed embodiments will be described in detail.

[0070] Figure 2 A flowchart illustrating an information generation method according to an embodiment of the present disclosure is shown schematically.

[0071] like Figure 2 As shown, the information generation method 200 of this embodiment includes operations S201 to S202.

[0072] In operation S201, based on the first target label, the first unit information corresponding to the first target label is filtered from the pre-built information database to obtain M first unit information, where M is an integer greater than or equal to 2.

[0073] The pre-constructed information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the first initial information. N is an integer greater than or equal to M.

[0074] According to embodiments of this disclosure, the first initial information may be source information generated in various fields. The first initial information may include policy information. Policy information may include business rule information.

[0075] For example, source information of business rules associated with different regions can be obtained; and the source information of business rules can be preprocessed to obtain initial information. Preprocessing may include: merging the source information of business rules and the corresponding regional business indicator rule information, and using ETL (Extract-Transform-Load, a data warehouse technology) to perform deduplication, garbage information cleaning, and multi-level information merging on the merged information.

[0076] According to embodiments of this disclosure, first unit information is obtained by minimizing and decomposing first initial information. A first target label corresponding to the first unit information can be obtained based on the first unit information. The first target label can characterize the label information of the type represented by the first unit information. The association between the first unit information and other first unit information can indicate that the first unit information and other first unit information are related and have an association relationship. Alternatively, the association between the first unit information and other first unit information can also indicate that the first unit information and other first unit information are unrelated and have no association relationship.

[0077] For example, the first unit information includes: unit information A, unit information B, unit information C, and unit information D. If unit information A is only related to unit information B, a true association exists: if the tag information of type A is the first target tag 1, and the tag information of type B is the first target tag 2, then the first information group can include unit information A, first target tag 1, and the association between unit information A and unit information B; or the first information group can include unit information B, first target tag 2, and the association between unit information B and unit information A. If unit information A is unrelated to unit information D, no association exists: if the tag information of type A is the first target tag 1, then the first information group can include unit information A, first target tag 1, and the association between unit information A and unit information D.

[0078] In operation S202, the M pieces of information are combined according to the relationship between them to generate target information.

[0079] According to embodiments of this disclosure, target information can be generated by arranging and combining the M first unit information according to the correlation between them. The target information can represent complete information.

[0080] For example, the first unit information can be obtained by minimizing and decomposing information rules. The first unit information, its corresponding first target label, and the relationships between the first unit information and other first unit information can be combined to form a first information group. This first information group is stored in an information database. When the business rule information system manages business rule information, it can filter the first unit information corresponding to the first target label from the information database, obtaining M first unit information pieces. Based on the relationships between these M first unit information pieces, they are combined to generate target information. Target information is the configuration information obtained after the business rule information system intelligently configures the business rule information. The business rule information system can also quickly invoke configurations using multiple pre-generated target information pieces. Furthermore, the business rule information system can also delete multiple pre-generated target information pieces.

[0081] According to the embodiments of this disclosure, by breaking down the information into its smallest units to obtain the first unit information, the problems of information redundancy or unreasonable information after configuration are avoided. Furthermore, according to multi-dimensional information groups, the first unit information, the first target tag corresponding to the first unit information, and the association relationships between the first unit information and other first unit information are stored in an information database. This facilitates the selection of first unit information from the database and the generation of target information, achieving intelligent information configuration, making configuration convenient and fast, and improving information configuration efficiency.

[0082] Figure 3 A flowchart illustrating an information generation method according to another embodiment of the present disclosure is shown schematically.

[0083] like Figure 3 As shown, the information generation method 300 of this embodiment may include operations S201 to S202, in addition to operations S201 to S202.

[0084] In operation S301, if it is determined that the second initial information has been obtained, T second information groups are obtained based on the second initial information. The second information group includes second unit information, second target label corresponding to the second unit information, and the association relationship between the second unit information and the second other unit information, where T is an integer greater than or equal to 1.

[0085] According to embodiments of this disclosure, information can be automatically acquired, and if the acquired current initial information is inconsistent with the first initial information, second initial information can be determined. Second unit information can be obtained by minimizing and decomposing the second initial information. A second target label corresponding to the second unit information can be obtained based on the second unit information. The second target label can represent the label information of the type represented by the second unit information. The association between the second unit information and other second unit information can indicate that the second unit information and other second unit information are related and have an association relationship. Alternatively, the association between the second unit information and other second unit information can also indicate that the second unit information and other second unit information are unrelated and have no association relationship.

[0086] In operation S302, if it is determined that there are differing information groups among the T second information groups based on the N first information groups, the information database is updated according to the differing information groups.

[0087] According to embodiments of this disclosure, it can be determined whether there are differing information groups among T second information groups based on N first information groups. If differing information groups exist, the information database is updated according to the differing information groups. If no differing information groups exist, the information database does not need to be updated.

[0088] For example, if the second unit information in the second information group differs from the first unit information in the first information group, then the second information group is a difference information group, and the information database needs to be updated based on the second information group. If the second information group contains both second unit information that differs from the first unit information in the first information group and a second target label corresponding to the second unit information in the second information group that differs from the first target label corresponding to the first unit information in the first information group, then the second information group is a difference information group, and the information database needs to be updated based on the second information group.

[0089] According to the embodiments of this disclosure, since the first initial information changes in real time, the current information database has a certain lag and needs to be updated periodically. A second information group is obtained based on the second initial information. By detecting the differences between the second information group and the first information group in the current information database, targeted and rapid updates to the information database are achieved. This ensures that the updated information group is not redundant, improves the efficiency of intelligent information configuration, and effectively avoids the drawback of consuming a large amount of manpower and material resources when modifying the information database.

[0090] According to another embodiment of this disclosure, in addition to operations S201-S202 and S301-S302, the information generation method may also include:

[0091] For the second information group among the T second information groups, if it is determined that there is no first information group among the N first information groups that matches the second information group, the second information group is determined as the difference information group.

[0092] According to embodiments of this disclosure, a second information group can be matched with all of the N first information groups, and if there is a mismatched second information group, it is determined to be a difference information group.

[0093] According to the embodiments of this disclosure, by determining whether there is a first information group among N first information groups that matches the second information group, the difference information group is determined, and then the information database is quickly updated for the difference information group, realizing real-time updating of the information database and saving a lot of manpower and material resources.

[0094] According to embodiments of this disclosure, when it is determined from N first information groups that there are differing information groups among T second information groups, updating the information database based on the differing information groups may include:

[0095] If, based on N first information groups, there are discrepancy information groups among T second information groups, the discrepancy level is obtained based on the discrepancy information groups; the update strategy corresponding to the discrepancy level is invoked; and the information database is updated based on the update strategy and the discrepancy information groups.

[0096] According to embodiments of this disclosure, the difference level can characterize the degree of difference between the difference information group and the first information group. The update strategy can characterize the update operation instructions for different difference levels. Different difference levels can correspond to different update strategies.

[0097] According to embodiments of this disclosure, by classifying the difference information group into difference levels, different update strategies can be adopted for different difference levels, which can improve the update speed and ensure the normal operation of the update method.

[0098] According to embodiments of this disclosure, the difference level may include a first difference level and a second difference level;

[0099] Updating the information database based on the update strategy and according to the difference information groups can include:

[0100] If the difference level is Level 1, the database is updated according to the difference information group. If the difference level is Level 2, an update request is sent to a third party so that the third party can determine the operation method based on the update request; and in response to receiving the operation method from the third party, the database is updated according to the difference information group based on the operation method.

[0101] According to embodiments of this disclosure, a first difference level can characterize a difference level where the degree of difference between the difference information group and the first information group is low. A second difference level can characterize a difference level where the degree of difference between the difference information group and the first information group is high.

[0102] For example, if a difference information group differs from the first information group only in that the second target label corresponding to the second unit information differs from the first target label corresponding to the first unit information, and all other aspects are the same, then the degree of difference can be considered low, and this difference information group belongs to the first level of difference. If a difference information group differs from the first information group not only in that the second unit information differs from the first unit information, but also in that the correlation between the second unit information and other second unit information differs from the correlation between the first unit information and other first unit information, then the degree of difference can be considered high, and this difference information group belongs to the second level of difference.

[0103] According to embodiments of this disclosure, for cases where the difference level is the first difference level, a low-level warning alert can be set, and the information database can be automatically updated based on the difference information group upon receiving the low-level warning alert. For cases where the difference level is the second difference level, a high-level warning alert can be set, and an update request can be sent to a third party upon receiving the high-level warning alert, so that the third party can determine the operation method based on the update request; in response to receiving the operation method from the third party, the information database is updated based on the operation method and the difference information group. An update operation log can be generated after the update is completed.

[0104] It should be noted that if no action is received from a third party within the scheduled time, the database can be automatically updated based on the difference information group to ensure the normal operation of the update. The scheduled time could be, for example, 24 hours.

[0105] According to embodiments of this disclosure, automatic updates have a high probability of error due to the different levels of difference. Automatic updates are performed for the first level of difference. For the second level of difference, updates are performed according to an operation method determined by a third party. This can improve update speed and ensure the normal operation of the update.

[0106] According to embodiments of this disclosure, the information generation method may further include:

[0107] The information in the first unit is parsed to obtain the parsing result; based on the parsing result, the initial label corresponding to the information in the first unit is determined; based on the category represented by the initial label, the target label corresponding to the initial label is determined; and the initial label corresponding to the information in the first unit is replaced with the target label corresponding to the initial label.

[0108] According to embodiments of this disclosure, the initial label can represent an information label that can be directly obtained based on the first unit information. The target label can represent an initial label of the same category.

[0109] For example, if the first unit of information contains educational registration information, the initial label could be "Education Level". Information such as degrees and diplomas from Chinese domestic universities with the "Education Level" label could be designated as the "Domestic Education" target label, while educational information from the US, Europe, etc., with the "Education Registration" label could be designated as the "Foreign Education" target label. Similarly, initial labels for "Work Injury Insurance Payment" or "Medical Insurance Payment" could be designated as "Social Security" or "Medical Insurance" target labels, and so on.

[0110] According to embodiments of this disclosure, by standardizing the initial tags to obtain the target tags, information tags can be standardized, which is beneficial for screening and combining during intelligent configuration.

[0111] According to embodiments of this disclosure, the information generation method may further include:

[0112] Based on the initial label, determine the association between the information in the first unit and the information in the first other units;

[0113] Based on the first unit information, the target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information, a first information group is obtained; and

[0114] Store the first information group in the information database.

[0115] According to embodiments of this disclosure, the first information group can be obtained using a multi-dimensional information storage method. The first unit information, the target tag corresponding to the first unit information, and the association relationships between the first unit information and other first unit information are combined to form a first information group with multi-dimensional information. This first information group with multi-dimensional information is then stored in an information database.

[0116] According to embodiments of this disclosure, the association between the first unit information and other first unit information is determined based on the initial label. For example, "domestic undergraduate" and "first-tier undergraduate" may be associated; "first-tier undergraduate" and "key undergraduate" may be associated; "key undergraduate" and "Double First-Class" may be associated; "legal and stable residence" and "owner-owned residence" may be associated; "owner-owned residence" and "owner-owned commercial residence" may be associated; "owner-owned commercial residence" and "owner-owned unit-provided housing" may be associated, etc.

[0117] According to embodiments of this disclosure, by storing information groups composed of multidimensional information in an information database, intelligent configuration can be performed through tags and associations during intelligent configuration, thereby improving the efficiency of information configuration.

[0118] Figure 4 The diagram illustrates an intelligent information configuration interaction flowchart according to an embodiment of the present disclosure.

[0119] like Figure 4 As shown, the intelligent information configuration interaction process 400 of this embodiment includes operations S401 to S407.

[0120] In operation S401, the first initial information is obtained.

[0121] According to embodiments of this disclosure, business rule information associated with different regions can be obtained from different regions.

[0122] In operation S402, the first initial information is minimized and disassembled to obtain the first unit information.

[0123] According to embodiments of this disclosure, after obtaining the first initial information in operation S401, a minimization disassembly is performed to obtain multiple first unit information.

[0124] For example, business rule information can be broken down into multiple first-unit information.

[0125] In operation S403, an information database with multi-dimensional information is obtained based on the information in the first unit.

[0126] According to embodiments of this disclosure, a first target tag corresponding to the first unit information and the association relationship between the first unit information and other first unit information can be obtained based on the acquired first unit information. The first unit information, the first target tag corresponding to the first unit information, and the association relationship between the first unit information and other first unit information can be combined into a first information group. The first information group is stored in an information database to obtain an information database with multi-dimensional information.

[0127] By operating the S404, intelligent configuration is performed to obtain target information.

[0128] According to embodiments of this disclosure, intelligent configuration information can be performed based on an information database with multi-dimensional information obtained in operation S403. Target information can be obtained by filtering first-unit information from the information database with multi-dimensional information and combining the first-unit information.

[0129] When operating S405, should a target information template library be created?

[0130] According to embodiments of this disclosure, it is determined whether to create a target information template library. If yes, operation S406 is executed. If no, operation S407 is executed.

[0131] In operation S406, a target information template library is created based on the target information.

[0132] According to embodiments of this disclosure, multiple target information can be obtained by re-executing the above-described operation S404. The multiple target information is stored in a target information template library for easy management. Management may include editing, deleting, and quick-accessing the target information template library. Quick-accessing the library allows for direct selection of target information from the target information template library during subsequent intelligent configuration.

[0133] According to embodiments of this disclosure, the first initial information may include policy information. The policy information may include business rule information.

[0134] Figure 5 The diagram illustrates the architecture of a business rules information system according to an embodiment of this disclosure.

[0135] like Figure 5 As shown, the business rules information system can be divided into 5 layers from bottom to top, with standards and specifications and information security protection systems running through each layer.

[0136] The presentation layer can be the front end of the business rules information system, providing a unified rule application platform for system operators on the PC.

[0137] The application layer can implement the main business functions of the business rules information system, including: information management, user management, permission management, rule application, business approval, form export, information configuration, report statistics, and log auditing. In the entire business rules, each specific business can be viewed as a single processing piece of information, facilitating unified management. The information configuration can be set according to the information generation method in this embodiment. For example, the information generation method includes: filtering first unit information corresponding to the first target tag from a pre-built information database based on the first target tag to obtain M first unit information pieces, where M is an integer greater than or equal to 2; and combining the M first unit information pieces according to the association relationships between them to generate target information.

[0138] The application support layer plays a crucial role in bridging the gap between the upper and lower layers, serving as the primary support for business processing. It provides identity authentication, log interception, workflow engine, and caching service platform.

[0139] The data resource layer stores various business rule information and distinguishes data based on different business scenarios, including a business database and an information database. Different data storage and access mechanisms are used according to the data and access characteristics requirements of different business scenarios, and relevant backup and optimization strategies are formulated to ensure the system's continuous service capability. The information database can be a pre-built information database in the information generation method of this embodiment. The pre-built information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the decomposition of the first initial information, and N is an integer greater than or equal to M.

[0140] The infrastructure layer supports deployment and operation in traditional environments and various cloud environments, and supports flexible horizontal scaling based on the operation of the information system according to business rules.

[0141] Figure 6 The diagram illustrates the internal technical architecture of a business rules information system according to an embodiment of the present disclosure.

[0142] like Figure 6As shown, the internal technical architecture of the business rules information system can be divided into a Web layer, an application layer, and a data layer. It can be implemented using the company's mainstream technology stacks and is provided to business personnel in a B / S architecture. The business rules information system has the ability to quickly process and respond to user requests and handle various rule application business. The core data information of various rule application business generated during operation is synchronously stored in the data layer. Utilizing the dependencies of the information database and the target information template database, the intelligent configuration of information in the business rules information system is ensured. The information database can be a pre-built information database in the information generation method of this embodiment. The pre-built information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the decomposition of the first initial information, and N is an integer greater than or equal to M. The target information template database can include multiple target information. The target information can be obtained according to the information generation method of this embodiment. For example, the information generation method includes: filtering first unit information corresponding to the first target label from a pre-constructed information database according to the first target label to obtain M first unit information, where M is an integer greater than or equal to 2; and combining the M first unit information according to the correlation between them to generate target information.

[0143] The Web layer can adopt a service component-based design and can use Vue + ElementUI + Echarts component library and various front-end technologies such as JS (JavaScript), Html (Hypertext Markup Language), and CSS (Cascading Style Sheets) to support the implementation of UI display and interaction logic on various platforms.

[0144] The application layer can build a basic framework, components, and parts based on Spring Boot, providing services in the form of RESTful APIs (interfaces that conform to the REST (Representational State Transfer) architectural style). Among them, the Activiti process engine supports task configuration and process scheduling; Quartz task scheduling supports services such as adding and configuring scheduled tasks; Mybatis data persistence supports data read and write services; Redis caching service supports read and write access to the cache database; log interception supports operation log trailing; and data exchange provides data exchange and transmission with related application systems. Through the above services, the implementation of various business logics and business processing procedures of the system is supported.

[0145] The data layer enables the storage of various types of business information data, differentiating information data based on different business scenarios within the business rules information system. Different data storage and access mechanisms are used according to the data and access characteristics requirements of different business scenarios, and relevant backup and optimization strategies are formulated to ensure the system's continuous service capabilities.

[0146] Based on the above information generation method, this disclosure also provides an information generation apparatus. The following will be combined with... Figure 7 The device is described in detail.

[0147] Figure 7 A schematic block diagram of an information generation apparatus according to an embodiment of the present disclosure is shown.

[0148] like Figure 7 As shown, the information generation device 700 of this embodiment includes a filtering module 710 and a combination module 720.

[0149] The filtering module 710 is used to filter first unit information corresponding to the first target label from a pre-built information database according to the first target label, to obtain M first unit information, where M is an integer greater than or equal to 2. In one embodiment, the filtering module 710 can be used to perform the operation S201 described above, which will not be repeated here.

[0150] The combination module 720 is used to combine the M first unit information pieces according to the association relationship between them to generate target information. In one embodiment, the combination module 720 can be used to perform the operation S202 described above, which will not be repeated here.

[0151] The pre-constructed information database includes N first information groups. Each first information group includes first unit information, a first target label corresponding to the first unit information, and the association relationship between the first unit information and other first unit information. The first unit information is obtained by minimizing the first initial information. N is an integer greater than or equal to M.

[0152] According to embodiments of this disclosure, the information generation apparatus 700 may further include: a first acquisition module and an update module.

[0153] The first acquisition module is used to obtain T second information groups based on the second initial information when it is determined that the second initial information has been obtained. The second information group includes second unit information, second target label corresponding to the second unit information, and the association relationship between the second unit information and the second other unit information, where T is an integer greater than or equal to 1.

[0154] The update module is used to update the information database based on the difference information groups when it is determined that there are difference information groups among T second information groups based on N first information groups.

[0155] According to embodiments of this disclosure, any plurality of modules in the screening module 710 and the combination module 720 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the screening module 710 and the combination module 720 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in any one of software, hardware, and firmware methods, or in a suitable combination of any of these. Alternatively, at least one of the screening module 710 and the combination module 720 may be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0156] Figure 8 A block diagram schematically illustrates an electronic device suitable for implementing an information generation method according to an embodiment of the present disclosure.

[0157] like Figure 8 As shown, an electronic device 800 according to an embodiment of this disclosure includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage portion 908 into a random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this disclosure.

[0158] RAM 803 stores various programs and data required for the operation of electronic device 800. Processor 801, ROM 802, and RAM 803 are interconnected via bus 804. Processor 801 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 802 and / or RAM 803. It should be noted that the programs may also be stored in one or more memories other than ROM 802 and RAM 803. Processor 801 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0159] According to embodiments of this disclosure, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to a bus 804. The electronic device 800 may also include one or more of the following components connected to the I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 810 as needed so that computer programs read from it can be installed into the storage section 808 as needed.

[0160] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0161] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 802 and / or RAM 803 and / or one or more memories other than ROM 802 and RAM 803 described above.

[0162] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this disclosure.

[0163] When the computer program is executed by the processor 801, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0164] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 809, and / or installed from a removable medium 811. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0165] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 809, and / or installed from removable medium 811. When the computer program is executed by processor 801, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0166] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0167] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0168] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0169] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An information generation method applied to a business rule information system, comprising: in a case where it is determined that a first initial information is managed, screening, according to a first target label, a first unit information corresponding to the first target label from a pre-constructed information base to obtain M first unit information, wherein M is an integer greater than or equal to 2; and combining, according to an association relationship between the M first unit information, the M first unit information to generate target information; wherein the pre-constructed information base comprises N first information groups, the first information group comprises the first unit information, a first target label corresponding to the first unit information and an association relationship between the first unit information and a first other unit information, the first unit information is obtained by minimally disassembling the first initial information, the first initial information is obtained by preprocessing a business rule source information, the business rule source information is information associated with a region obtained from different regions, and N is an integer greater than or equal to M.

2. The method of claim 1, further comprising: in a case where it is determined that a second initial information is obtained, obtaining, according to the second initial information, T second information groups, the second information group comprising a second unit information, a second target label corresponding to the second unit information and an association relationship between the second unit information and a second other unit information, wherein T is an integer greater than or equal to 1; and in a case where it is determined that there is a difference information group in the T second information groups according to the N first information groups, updating the information base according to the difference information group.

3. The method of claim 2, further comprising: for the second information group in the T second information groups, in a case where it is determined that there is no first information group in the N first information groups that matches the second information group, determining the second information group as the difference information group.

4. The method of claim 2 or 3, wherein, The updating the information base according to the difference information group in a case where it is determined that there is a difference information group in the T second information groups according to the N first information groups comprises: in a case where it is determined that there is a difference information group in the T second information groups according to the N first information groups, obtaining a difference level according to the difference information group; calling an update strategy corresponding to the difference level; and updating the information base according to the difference information group based on the update strategy.

5. The method of claim 4, wherein, The difference level comprises a first difference level and a second difference level; wherein the updating the information base according to the difference information group based on the update strategy comprises: in a case where the difference level is the first difference level, updating the information base according to the difference information group; in a case where the difference level is the second difference level, sending an update request to a third party so that the third party determines an operation mode according to the update request; and in response to receiving the operation mode from the third party, updating the information base according to the difference information group based on the operation mode.

4. An information generation system applied to a business rule information system, comprising: a first unit information screening unit configured to, in a case where it is determined that a first initial information is managed, screen, according to a first target label, a first unit information corresponding to the first target label from a pre-constructed information base to obtain M first unit information, wherein M is an integer greater than or equal to 2; and a first unit information combining unit configured to combine, according to an association relationship between the M first unit information, the M first unit information to generate target information; wherein the pre-constructed information base comprises N first information groups, the first information group comprises the first unit information, a first target label corresponding to the first unit information and an association relationship between the first unit information and a first other unit information, the first unit information is obtained by minimally disassembling the first initial information, the first initial information is obtained by preprocessing a business rule source information, the business rule source information is information associated with a region obtained from different regions, and N is an integer greater than or equal to M.

5. The system of claim 4, further comprising: a second information group obtaining unit configured to, in a case where it is determined that a second initial information is obtained, obtain, according to the second initial information, T second information groups, the second information group comprising a second unit information, a second target label corresponding to the second unit information and an association relationship between the second unit information and a second other unit information, wherein T is an integer greater than or equal to 1; and an information base updating unit configured to, in a case where it is determined that there is a difference information group in the T second information groups according to the N first information groups, update the information base according to the difference information group.

6. The system of claim 5, further comprising: a difference information group determining unit configured to, for the second information group in the T second information groups, in a case where it is determined that there is no first information group in the N first information groups that matches the second information group, determine the second information group as the difference information group. The information base updating unit is configured to, in a case where it is determined that there is a difference information group in the T second information groups according to the N first information groups, obtain a difference level according to the difference information group, call an update strategy corresponding to the difference level, and update the information base according to the difference information group based on the update strategy. The difference level comprises a first difference level and a second difference level. The information base updating unit is configured to, in a case where the difference level is the first difference level, update the information base according to the difference information group, in a case where the difference level is the second difference level, send an update request to a third party so that the third party determines an operation mode according to the update request, and in response to receiving the operation mode from the third party, update the information base according to the difference information group based on the operation mode. 6.The method of claim 1 or 2, further comprising: parsing the first unit information to obtain a parsing result; determining an initial label corresponding to the first unit information according to the parsing result; determining a target label corresponding to the initial label according to a category represented by the initial label; and replacing the initial label corresponding to the first unit information with the target label corresponding to the initial label. 7.The method of claim 6, further comprising: determining an association relationship between the first unit information and the first other unit information according to the initial label; obtaining the first information group according to the first unit information, the target label corresponding to the first unit information, and the association relationship between the first unit information and the first other unit information; and storing the first information group in the information base. The first initial information comprises policy information. 9.An information generation apparatus applied to a business rule information system, comprising:

8. The method of claim 1 or 2, wherein, a screening module configured to, in a case where it is determined that a first initial information is managed, screen, according to a first target label, M first unit information corresponding to the first target label from a pre-constructed information base, wherein M is an integer greater than or equal to 2; and a combination module configured to combine M first unit information according to an association relationship between the M first unit information, to generate target information; wherein the pre-constructed information base comprises N first information groups, the first information group comprises the first unit information, a first target label corresponding to the first unit information, and an association relationship between the first unit information and a first other unit information, the first unit information is obtained by minimizing and disassembling the first initial information, the first initial information is obtained by preprocessing business rule source information, the business rule source information is information associated with a region obtained from different regions, and N is an integer greater than or equal to M. 10.An electronic device comprising: one or more processors; a storage device configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method according to any one of claims 1-8. 11.A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1-8. 12.A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-8. ​ ​

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