CN111078202A

CN111078202A - Service architecture model maintenance method, device, electronic equipment and medium

Info

Publication number: CN111078202A
Application number: CN201911241596.3A
Authority: CN
Inventors: 方红; 李娜; 王欢; 李曼
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2019-12-06
Filing date: 2019-12-06
Publication date: 2020-04-28

Abstract

The present disclosure provides a service architecture model maintenance method, device, electronic device and medium, the maintenance method includes: obtaining maintenance information, wherein the maintenance information comprises a model to be maintained; determining a maintenance instruction corresponding to the maintenance information, wherein the maintenance instruction comprises a first maintenance instruction for a model to be maintained and a second maintenance instruction for an associated model, and the associated model is a model related to the model to be maintained in the business architecture; and responding to the first maintenance instruction and the second maintenance instruction, and maintaining the model to be maintained and the associated model.

Description

Service architecture model maintenance method, device, electronic equipment and medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for maintaining a business architecture model, an electronic device, and a medium.

Background

At present, with the continuous development of enterprise-level business architecture, a business model of the enterprise-level business architecture is constructed based on entities, processes and products, and the business model can provide guiding significance for enterprise decision from multiple angles.

In the existing enterprise-level business architecture, when a business model is maintained each time, a maintainer needs to establish an application online to manually change the business model, and needs users with different authorities to perform examination and approval.

In carrying out the presently disclosed concept, the inventors have found that there are at least the following problems in the related art. When the related technology maintains the service model, the process is complicated and the workload is huge, and the maintenance errors are easy to occur. In addition, in the service model maintenance process, maintenance personnel need to maintain the model based on own professional knowledge, but the maintenance of part of the model may affect the models in other fields, and if the maintenance personnel do not know the models in other fields, the maintenance personnel cannot work.

Disclosure of Invention

In view of the above, the present disclosure provides a service architecture model maintenance method, apparatus, electronic device, and medium for reducing maintenance difficulty and improving maintenance operation accuracy.

One aspect of the present disclosure provides a service architecture model maintenance method, including: obtaining maintenance information, wherein the maintenance information comprises a model to be maintained; determining a maintenance instruction corresponding to the maintenance information, wherein the maintenance instruction comprises a first maintenance instruction for a model to be maintained and a second maintenance instruction for an associated model, and the associated model is a model related to the model to be maintained in the business architecture; and responding to the first maintenance instruction and the second maintenance instruction, and maintaining the model to be maintained and the associated model.

According to the business architecture model maintenance method provided by the embodiment of the disclosure, the real intention of a user is analyzed according to the model maintenance requirement, and the related model modification item and the corresponding maintenance instruction are mapped according to the modification point and the configuration file, so that the embodiment of the disclosure can automatically complete model modification. Compared with the traditional manual model maintenance, the maintenance efficiency and the maintenance accuracy of the business model are effectively improved, and the difficulty of maintenance work can be reduced.

According to an embodiment of the present disclosure, determining a maintenance instruction corresponding to the maintenance information includes: for the maintenance information of the text type, segmenting the maintenance information of the text type based on a service model segmentation word library to obtain a segmentation result, wherein the segmentation result comprises at least one of operation type segmentation, asset type segmentation and semantic mode; determining an operation scheme based on the word segmentation result; and determining a maintenance instruction based on the operation scheme and the database task model, wherein the database task model comprises a mapping relation between the operation scheme and the maintenance instruction.

According to the embodiment of the disclosure, the service model word segmentation word bank comprises: at least one of a business model operation class word library, a business model asset class word library and a business model instance class word library; performing word segmentation on the maintenance information of the text type based on a service model word segmentation word bank to obtain word segmentation results, wherein the word segmentation results comprise: matching the words in the maintenance information with the operation class word segmentation word library of the service model respectively to obtain operation class words; matching the words in the maintenance information with the asset class word banks of the service model respectively to obtain asset class words; and determining a semantic schema based on the operation class terms and the asset class terms.

According to an embodiment of the present disclosure, determining an operation scheme based on a word segmentation result includes: determining a current semantic template based on the similarity between the semantic mode and a semantic template in a maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable; and determining an operation scheme for the model to be maintained and the associated model based on the operation class words, the asset class words and the current semantic template.

According to the embodiment of the disclosure, the similarity includes a structural similarity and a semantic similarity, and the sum of the weights of the structural similarity and the semantic similarity is 100%.

According to an embodiment of the present disclosure, the structural similarity includes: at least one of the similarity of word shape, the similarity of word order and the similarity of sentence length.

According to an embodiment of the disclosure, determining an operation scheme for the model to be maintained and the associated model based on the operation class words, the asset class words, and the current semantic template includes: filling the current semantic template with operation words and asset words to obtain an operation scheme for the model to be maintained; and determining an operating scenario for the associated model, the associated model corresponding to the model to be maintained.

According to an embodiment of the disclosure, the method further comprises: after obtaining the maintenance information, for the maintenance information of the voice type, obtaining a voice recognition result of the maintenance information of the voice type to obtain the maintenance information of the text type corresponding to the maintenance information of the voice type.

According to an embodiment of the disclosure, the method further comprises: and updating the service model word segmentation word bank based on the updating information of the service architecture.

According to an embodiment of the disclosure, the method further comprises: and after the model to be maintained and the association model are maintained, outputting a maintenance result.

One aspect of the present disclosure provides an internet technology architecture construction apparatus, including: the system comprises a maintenance information obtaining module, a maintenance instruction determining module and a maintenance module. The maintenance information acquisition module is used for acquiring maintenance information, and the maintenance information comprises a model to be maintained; the maintenance instruction determining module is used for determining a maintenance instruction corresponding to the maintenance information, wherein the maintenance instruction comprises a first maintenance instruction for a model to be maintained and a second maintenance instruction for an associated model, and the associated model is a model related to the model to be maintained in the service architecture; and the maintenance module is used for responding to the first maintenance instruction and the second maintenance instruction and maintaining the model to be maintained and the associated model.

According to an embodiment of the present disclosure, the maintenance instruction determining module includes: the system comprises a word segmentation sub-module, a scheme determination sub-module and an instruction determination sub-module. The word segmentation submodule is used for segmenting the maintenance information of the text type based on the business model word segmentation word bank to obtain a word segmentation result, and the word segmentation result comprises at least one of operation class word segmentation, asset class word segmentation and semantic mode; the scheme determining submodule is used for determining an operation scheme based on the word segmentation result; and the instruction determining submodule is used for determining a maintenance instruction based on the operation scheme and the database task model, wherein the database task model comprises a mapping relation between the operation scheme and the maintenance instruction.

According to an embodiment of the present disclosure, the word segmentation submodule includes: a word obtaining unit and a semantic mode determining unit. The word obtaining unit is used for matching the words in the maintenance information with the operation class word-classifying lexicon of the service model respectively to obtain operation class words, and matching the words in the maintenance information with the asset class lexicon of the service model respectively to obtain asset class words. The semantic mode determining unit is used for determining a semantic mode based on the operation class words and the asset class words.

According to an embodiment of the present disclosure, the scheme determination submodule includes: a semantic template determining unit and a scheme determining unit. The semantic template determining unit is used for determining a current semantic template based on the similarity between the semantic mode and the semantic template in the maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable. The scheme determining unit is used for determining an operation scheme for the model to be maintained and the associated model based on the operation class words, the asset class words and the current semantic template.

According to an embodiment of the present disclosure, the scheme determining unit includes: the template population subunit and the association scheme determination subunit. The template filling subunit is used for filling the current semantic template with the operation words and the asset words to obtain an operation scheme for the model to be maintained. The association scheme determining subunit is used for determining an operation scheme for an association model, and the association model corresponds to the model to be maintained.

According to the embodiment of the disclosure, the device further comprises an updating module, wherein the updating module is used for updating the business model word segmentation word bank based on the updating information of the business architecture.

According to an embodiment of the present disclosure, the apparatus further comprises a maintenance result output module. The maintenance result output module is used for outputting a maintenance result after the model to be maintained and the associated model are maintained.

Another aspect of the present disclosure provides a business architecture model maintenance system, including: the system comprises a business model asset management and control system, a semantic analysis system and a business model maintenance strategy system. The business model asset management and control system is used for storing a business model of a business architecture, sending obtained maintenance information to the semantic analysis system, and maintaining the business model according to a maintenance instruction uploaded by the business model maintenance strategy system; the semantic analysis system is used for processing the maintenance information based on the service model word segmentation word bank so as to obtain a word segmentation result of the maintenance information; and the service model maintenance strategy system is used for determining a maintenance instruction based on the word segmentation result and the database task model and sending the maintenance instruction to the service model asset management and control system.

Another aspect of the present disclosure provides an electronic device comprising one or more processors and a storage for storing executable instructions that, when executed by the processors, implement the method as described above.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.

Another aspect of the disclosure provides a computer program comprising computer executable instructions for implementing the method as described above when executed.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

fig. 1 schematically illustrates a business architecture model maintenance method, an internet technology architecture construction apparatus, and an application scenario of an electronic device according to an embodiment of the present disclosure;

fig. 2 schematically shows an exemplary system architecture of a building apparatus of an internet technology architecture to which a business architecture model maintenance method can be applied, according to an embodiment of the present disclosure;

FIG. 3 schematically illustrates a flow chart of a business architecture model maintenance method according to an embodiment of the present disclosure;

FIG. 4 schematically shows a business architecture diagram according to an embodiment of the disclosure;

FIG. 5 schematically illustrates a flow chart for determining a maintenance instruction corresponding to maintenance information, in accordance with an embodiment of the present disclosure;

FIG. 6 schematically illustrates a flow diagram of a business architecture model maintenance method according to another embodiment of the present disclosure;

FIG. 7 schematically illustrates a block diagram of a business architecture model maintenance apparatus according to an embodiment of the present disclosure;

FIG. 8 schematically illustrates a block diagram of a business architecture model maintenance apparatus according to another embodiment of the present disclosure;

FIG. 9 schematically illustrates a block diagram of a business architecture model maintenance system according to an embodiment of the present disclosure; and

FIG. 10 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features.

The embodiment of the disclosure provides a service architecture model maintenance method, a service architecture model maintenance device, electronic equipment and a medium. The business architecture model maintenance method comprises a service maintenance instruction determining process and a maintenance process. In the service maintenance instruction determining process, firstly, maintenance information is obtained, the maintenance information comprises a model to be maintained, then, a maintenance instruction corresponding to the maintenance information is determined, wherein the maintenance instruction comprises a first maintenance instruction aiming at the model to be maintained and a second maintenance instruction aiming at an associated model, and the associated model is a model related to the model to be maintained in a business architecture. And after the service maintenance instruction determining process is completed, entering a maintenance process, and responding to the first maintenance instruction and the second maintenance instruction to maintain the model to be maintained and the association model.

Fig. 1 schematically shows a business architecture model maintenance method, an internet technology architecture construction device, and an application scenario of an electronic device according to an embodiment of the present disclosure.

As shown in fig. 1, in the related art, a business architecture includes a plurality of models, such as models 1, 2, 3, 4, and 5. There is a relationship between multiple models, for example, the input of model 3 in fig. 1 may depend on the outputs of model 1 and model 2, and the output of model 3 may in turn be the dependence of the inputs of model 4 and model 5. When the model 3 needs to be updated, such as changing its calling relationship, the model related to the model 3 may be affected. Therefore, when modifying the model 3, the model related to the model needs to be modified, so as to avoid that the modification of the model 3 causes the models 1, 2, 4, 5, etc. to be affected and not to work normally.

According to the service architecture model maintenance method, the service architecture model maintenance device, the electronic equipment and the service architecture model maintenance medium, after the maintenance information is obtained, the maintenance instruction of the to-be-maintained model and the related associated model corresponding to the maintenance information is automatically determined, so that maintenance personnel do not need to judge the model needing to be maintained according to the knowledge base of the maintenance personnel, the maintenance difficulty is reduced, and the problem that the service architecture model cannot work normally due to maintenance operation errors can be effectively reduced.

Fig. 2 schematically shows an exemplary system architecture of a building apparatus to which a business architecture model maintenance method, an internet technology architecture, according to an embodiment of the present disclosure can be applied. It should be noted that fig. 2 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.

As shown in fig. 2, the system architecture 200 according to this embodiment may include

terminal devices

201, 202, 203, a network 204 and a server 205. The network 204 may include a plurality of gateways, routers, hubs, network wires, etc. to provide a medium for communication links between the

end devices

201, 202, 203 and the server 205. Network 204 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

201, 202, 203 to interact with other terminal devices and the server 205 via the network 204 to receive or send information and the like, such as sending service requests and receiving processing results and the like. The

terminal devices

201, 202, 203 may be installed with various communication client applications, such as a bank application, a monitoring application, an operation and maintenance application, a web browser application, a search application, an office application, an instant messaging tool, a mailbox client, social platform software, and other applications (for example only).

The

terminal devices

201, 202, 203 include, but are not limited to, smart phones, virtual reality devices, augmented reality devices, tablets, laptop computers, and the like.

The server 205 may receive the request and process the request. For example, the server 205 may be a back office management server, a cluster of servers, or the like. The background management server may analyze and process the received service request, information request, model management request, and the like, and feed back a processing result (such as requested information, operation and maintenance result, service result, and the like) to the terminal device.

It should be noted that the model maintenance method provided by the embodiment of the present disclosure may be generally performed by the server 205. Accordingly, the model maintenance apparatus provided by the embodiments of the present disclosure may be generally disposed in the server 205. The model maintenance method provided by the embodiment of the present disclosure may also be performed by a server or a server cluster that is different from the server 205 and is capable of communicating with the

terminal devices

201, 202, 203 and/or the server 205.

It should be understood that the number of terminal devices, networks, and servers are merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

FIG. 3 schematically shows a flow chart of a business architecture model maintenance method according to an embodiment of the disclosure.

As shown in fig. 3, the method may include operations S301 to S305.

In operation S301, maintenance information is obtained, the maintenance information including a model to be maintained.

In this embodiment, the user may input the maintenance information on the user side and send the maintenance information to the server side. The maintenance information may be text information or voice information, which is not limited herein.

In operation S303, a maintenance instruction corresponding to the maintenance information is determined, where the maintenance instruction includes a first maintenance instruction for a model to be maintained and a second maintenance instruction for an association model, and the association model is a model related to the model to be maintained in the service architecture.

In this embodiment, the maintenance instruction corresponding to the maintenance information may be determined based on a maintenance policy model constructed in advance. The maintenance instruction not only comprises the model to be maintained, but also comprises the association model which has association relation with the model to be maintained.

For example, the model base creates a semantic pattern by expert analysis of the service architecture-maintenance scheme-correspondence between database task models (e.g., delete service object-delete a service object & & delete all entities under a service object-create delete a service object and delete data task of all entities under a service object) and verifies according to the "updated requirements-data operation task" data for all histories. The maintenance strategy model corresponds all the maintenance requirements of addition, deletion and modification to the tasks of the system database. Such as add entity attribute-add entity (variable a) attribute (variable B) -data manipulation task entity (variable a) add attribute (variable B); adjusting an entity under a business object to the business object, deleting the relation between the business object (variable A) and the entity (variable B), and adding the relation between the business object (variable C) and the entity (variable B), deleting the relation between the business object (variable A) and the entity (variable B), and adding the business object (variable C) and the entity (variable B) by the data operation task; adding a task component between tasks in the activity, deleting the relationship between the task (variable B) and the task (variable C) of the activity (A) and the new activity (A), and the relationship between the task (variable B) and the task (variable D), and the relationship between the task (variable C) and the task (variable D), and deleting the relationship between the task (variable B) and the task (variable C) of the activity (A) and the new activity (A), and the relationship between the task (variable B) and the task (variable D) of the new activity (A), and the relationship between the task (variable C) and the task (variable D). Wherein & & represents AND.

For example, the business architecture may include an entity model, an activity model, a task model, a component model, and a product model, wherein the activity model, the task model, and the component model provide services for an entity corresponding to the entity model, a one-to-one or one-to-many first mapping relationship exists between the activity model and the task model, and a one-to-one or one-to-many second mapping relationship exists between the task model and the component model.

In this embodiment, the service framework may be a service framework constructed in advance. The construction process of the business architecture can be as follows.

Firstly, the business field of a business architecture is divided according to multiple dimensions based on a value stream, and multiple value chains for the multiple dimensions are obtained respectively. The business mode of an enterprise (such as a commercial bank) is analyzed, and business fields are divided according to different value streams, so that components of the business fields in multiple dimensions can be obtained conveniently. For example, the division may be done in stages according to the dimension of activities, tasks, steps. Specifically, the plurality of value chains for the plurality of dimensions includes: the activity value chain (corresponding to the activity model), the task flow (corresponding to the task model) and the operation component (corresponding to the component model), wherein the activity value chain comprises at least one task flow, and the task flow comprises at least one operation component. Wherein the activity value chain comprises an activity start point and an activity end point, the activity value chain being associated with a plurality of entities. The task process corresponds to a business process, and the business process corresponds to at least one service and serves one entity. The operation components correspond to one entity and one service.

Entities associated with each value chain and products required by the entities are then obtained. In particular, entities and products required by the entities, such as financial products, associated with each value chain may be determined and obtained based on the business architecture.

Then, respectively aiming at the value chain, the entity and the product of a plurality of dimensions, a business model, an entity model and a product model aiming at the plurality of dimensions are constructed, wherein a one-to-one or one-to-many mapping relation exists between the entity and the entity model of the business field, and a one-to-one or one-to-many mapping relation exists between the product and the product model of the business field. Each model can correspond to a file, and a user can conveniently call, operate, update and the like from the product device. Therefore, the whole business architecture can utilize a plurality of models stored in the product device to carry out business operation and construction of the Internet technology architecture.

And then, storing the constructed business model, entity model and product model so as to facilitate the construction of the Internet technology architecture based on at least one of the business model, the entity model and the product model. For example, when a service request is received, a model corresponding to the service request may be requested from the server side for local processing, or the server side may process the service request based on the model. As another example, when a business architecture is updated, the corresponding model may be updated for the updated portion such that the IT architecture and business architecture remain consistent. For another example, when a new product is developed, a required model can be called from a server according to product definition, and the model is assembled to effectively reduce the product development time and improve the model reuse rate.

The maintenance method of the business architecture can lead the business architecture (such as a commercial banking architecture) to have detailed asset classification and close information linkage, and can clearly provide a business architecture view. Through engineering means such as business architecture top layer design, model construction, information system landing and the like, the method has obvious effects on the aspects of creating an intelligent system, innovating key product service, simplifying business process business, subdividing user service, intelligent and accurate marketing, data information management, supporting operation analysis, optimizing performance assessment, improving system regulation and the like, and provides powerful support for improving benefit contribution degree, market competitiveness and user satisfaction degree.

Fig. 4 schematically shows a business architecture diagram according to an embodiment of the disclosure.

As shown in fig. 4, the business architecture includes an entity model, an activity model (corresponding to activity in the left diagram of fig. 4), a task model (corresponding to task group in the left diagram of fig. 4), and a component model (corresponding to task component (TTD for short) in the left diagram of fig. 4), where the activity model, the task model, and the component model provide services for entities corresponding to the entity model, a one-to-one or one-to-many first mapping relationship exists between the activity model and the task model, and a one-to-one or one-to-many second mapping relationship exists between the task model and the component model.

In operation S305, the model to be maintained and the associated model are maintained in response to the first maintenance instruction and the second maintenance instruction.

The model maintenance method provided by the embodiment of the disclosure processes the obtained maintenance information to obtain the maintenance instruction corresponding to the maintenance information, wherein the maintenance instruction includes a first maintenance instruction for the model to be maintained and a second maintenance instruction for the associated model, and the associated model is a model related to the model to be maintained in the service architecture, so that the embodiment of the disclosure can maintain the model to be maintained and the associated model based on the first maintenance instruction and the second maintenance instruction, thereby improving the automation degree of maintenance, being beneficial to reducing the dependence of the maintenance personnel on the knowledge base, reducing the probability of maintenance errors, and reducing the operation difficulty of the maintenance personnel.

Fig. 5 schematically illustrates a flow chart for determining a maintenance instruction corresponding to maintenance information according to an embodiment of the present disclosure.

As shown in fig. 5, for the text type of maintenance information, determining the maintenance instruction corresponding to the maintenance information may include operations S501 to S505.

In operation S501, a word segmentation result is obtained by performing word segmentation on the maintenance information of the text type based on the service model word segmentation lexicon, where the word segmentation result includes at least one of operation-class word segmentation, asset-class word segmentation, and semantic mode.

Specifically, the service model word segmentation word bank comprises: at least one of a business model operation class word library, a business model asset class word library and a business model instance class word library. The business model asset class lexicon and the business model instance class lexicon have one-to-one or one-to-many mapping relation, namely, assets of different types correspond to different business model instance class lexicons. It should be noted that the word segmentation result may also include a word obtained by performing word segmentation using a word segmentation lexicon of related technologies, which is not limited herein.

Correspondingly, performing word segmentation on the maintenance information of the text type based on the service model word segmentation word bank to obtain a word segmentation result may include the following operations.

Firstly, matching the word in the maintenance information with the operation class word-classifying base of the service model respectively to obtain operation class words, and matching the word in the maintenance information with the asset class word-classifying base of the service model respectively to obtain asset class words. In addition, the asset class words can be matched in the corresponding business model instance class word library to obtain instance class words.

Then, a semantic schema is determined based on the operation class terms and the asset class terms.

For example, Chinese text can be participled according to a word segmentation word bank and a word segmentation strategy of a business model. The service model word segmentation word bank comprises operation type word segmentation such as 'modification', 'deletion', 'addition', and the like; the asset class participles are asset type participles such as "business object", "entity", "task group", "task component", "attribute", and the like. The type word segmentation entity is such as 'order taking order' and the like, and the maintenance of the word stock can be updated in real time through the crawler asset management and control system. The word segmentation strategy is as follows: firstly, each word in the input Chinese sentence is matched with the dictionary in sequence, if the word is found in the dictionary, the matching is successful, and a boundary mark is added. For example, user input: deleting the return mark attribute under the return information entity of the order receiving order under the order receiving order business object, wherein the word segmentation result is as follows: delete/order take/business object/order take/return information/entity/order take/return flag/attribute. Then, words which are irrelevant to semantics, such as words, symbols and the like, are removed from the word segmentation result to obtain Chinese word segmentation semantics deletion/order receiving/business object/order receiving/goods returning information/entity/goods returning mark/attribute. Then, the operation class participle and the asset class participle in the Chinese participle word meaning are extracted to obtain a semantic mode, such as deletion/business object/entity/attribute.

In operation S503, an operation scheme is determined based on the word segmentation result.

Specifically, determining the operation scheme based on the word segmentation result may include the following operations.

Firstly, determining a current semantic template based on the similarity between the semantic mode and the semantic template in the maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable.

The similarity may include a structural similarity and a semantic similarity, and a sum of weights of the structural similarity and the semantic similarity is 100%.

In another embodiment, the structural similarity includes: at least one of the similarity of word shape, the similarity of word order and the similarity of sentence length.

Then, an operating scheme for the model to be maintained and the associated model is determined based on the operation class terms, the asset class terms, and the current semantic template.

For example, determining an operational scenario for the model to be maintained and the associated model based on the operation class terms, the asset class terms, and the current semantic template may include the following operations.

And filling the current semantic template with the operation words and the asset words to obtain an operation scheme for the model to be maintained. Wherein, when there are also instance class words, the instance class words can be filled in the current semantic template.

An operating scheme for an association model is determined, the association model corresponding to the model to be maintained.

In a specific embodiment, according to the Chinese word segmentation result, similarity matching is carried out on the input semantic mode and the semantic template in the model, and the template with the maximum similarity to the input is found. And supplementing the variables according to the Chinese word segmentation semantics to obtain a database execution task aiming at the model to be maintained. Specifically, first, the structural similarity of two sentences may be calculated, which comprehensively considers the shape of a word, the order of a word, and the length Sim1 (S)₁,S₂)＝p*Sim1₁(S₁,S₂)+q*Sim1₂(S₁，S₂)+rSim1₃(S₁,S₂) Wherein p, q and r are adjustable parameters and respectively represent weights of word shapes, word orders and sentence length similarity, and p + q + r is 1; sim1₁(S₁,S₂) Sim1 for word shape similarity₂(S₁，S₂) For word order similarity, Sim1₃(S₁,S₂) The sentence length similarity. Then, the total similarity Sim (S) of the two sentences is calculated₁,S₂)＝a*Sim1(S₁,S₂)+b*Sim2(S₁，S₂) Where a and b are adjustable parameters respectively representing the weights of structural similarity and semantic similarity, where a + b is 1, Sim1 (S)₁,S₂) For structural similarity, Sim2 (S)₁，S₂) Is semantic similarity. And then, selecting the semantic template corresponding to the highest value in the candidate items with the similarity greater than a specified threshold value, such as greater than 0.9.

In operation S505, a maintenance instruction is determined based on the operation scheme and the database task model, wherein the database task model includes a mapping relationship between the operation scheme and the maintenance instruction.

The database task model may be pre-constructed by an expert, the database task model including a correspondence between a model to be maintained-an operation scenario for the model to be maintained-an association model-an operation scenario for the association model. That is, after the first operating scenario for the model to be maintained is obtained, the second operating scenario for the associated model may be obtained. In this way, embodiments of the present disclosure may obtain, based on the maintenance information, a first operation scenario for the model to be maintained and a second operation scenario for the associated model, so as to obtain a first maintenance instruction and a second maintenance instruction corresponding to the first operation method and the second operation scenario.

In another embodiment, the method further comprises: after obtaining the maintenance information, for the maintenance information of the voice type, obtaining a voice recognition result of the maintenance information of the voice type to obtain the maintenance information of the text type corresponding to the maintenance information of the voice type.

The voice recognition may be implemented at the server side, or may be implemented at a server side specially providing a voice recognition function, which is not limited herein.

Therefore, the use convenience of a user is improved, and the model maintenance is realized in a voice mode.

In another embodiment, the method may further include the following operations.

And updating the service model word segmentation word bank based on the updating information of the service architecture.

Specifically, the service model word segmentation word library can be maintained by crawling the service model of the service architecture by using a crawler technology to update the service model word segmentation word library, such as updating a service architecture operation class word library, a service architecture asset class word library and a service architecture instance class word library.

According to the model maintenance method provided by the embodiment of the disclosure, a maintainer only needs to input a specific change requirement to automatically complete model updating. The labor cost is reduced, and the model maintenance efficiency is improved. Based on semantic information obtained by the service model word segmentation word bank, the modification intention of a user for a service model of a service architecture can be efficiently identified, and a model modification point can be more accurately analyzed. Effectively improve the problem that the error rate is high that manual operation leads to.

FIG. 6 schematically shows a flow diagram of a business architecture model maintenance method according to another embodiment of the present disclosure.

As shown in fig. 6, the method may further include an operation S601 after performing the operation S305 to maintain the model to be maintained and the associated model.

In operation S601, a maintenance result is output. For example, prompt information such as whether the maintenance is successful or not, whether maintenance is abnormal or not may be output, and information such as whether the user has finished the maintenance or not may be prompted.

One aspect of the present disclosure provides a business architecture model maintenance apparatus. FIG. 7 schematically shows a block diagram of a business architecture model maintenance apparatus according to an embodiment of the present disclosure.

As shown in fig. 7, the business architecture model maintenance apparatus 700 includes a maintenance information obtaining module 710, a maintenance instruction determining module 730, and a maintenance module 750.

The maintenance information obtaining module 710 is configured to obtain maintenance information, where the maintenance information includes a model to be maintained.

The maintenance instruction determining module 730 is configured to determine a maintenance instruction corresponding to the maintenance information, where the maintenance instruction includes a first maintenance instruction for a model to be maintained and a second maintenance instruction for an association model, and the association model is a model related to the model to be maintained in the service architecture.

The maintenance module 750 is configured to maintain the to-be-maintained model and the associated model in response to the first maintenance instruction and the second maintenance instruction.

In one embodiment, the maintenance order determination module 730 may include: the system comprises a word segmentation sub-module, a scheme determination sub-module and an instruction determination sub-module.

The word segmentation submodule is used for segmenting the maintenance information of the text type based on the business model word segmentation word bank to obtain a word segmentation result, and the word segmentation result comprises at least one of operation type word segmentation, asset type word segmentation and semantic mode.

And the scheme determination submodule is used for determining an operation scheme based on the word segmentation result.

The instruction determining submodule is used for determining a maintenance instruction based on the operation scheme and the database task model, wherein the database task model comprises a mapping relation between the operation scheme and the maintenance instruction.

Optionally, the word segmentation sub-module may include: a word obtaining unit and a semantic mode determining unit.

The word obtaining unit is used for matching the words in the maintenance information with the operation class word-classifying lexicon of the service model respectively to obtain operation class words, and matching the words in the maintenance information with the asset class lexicon of the service model respectively to obtain asset class words.

The semantic mode determining unit is used for determining a semantic mode based on the operation class words and the asset class words.

Optionally, the scheme determination submodule includes: a semantic template determining unit and a scheme determining unit.

The semantic template determining unit is used for determining a current semantic template based on the similarity between the semantic mode and the semantic template in the maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable.

The scheme determining unit is used for determining an operation scheme for the model to be maintained and the associated model based on the operation class words, the asset class words and the current semantic template.

For example, the similarity may include a structural similarity and a semantic similarity, and the sum of the weights of the structural similarity and the semantic similarity is 100%.

Specifically, the structural similarity may include: at least one of the similarity of word shape, the similarity of word order and the similarity of sentence length.

For another example, the scheme determination unit may include: the template population subunit and the association scheme determination subunit.

The template filling subunit is used for filling the current semantic template with the operation words and the asset words to obtain an operation scheme for the model to be maintained.

The association scheme determining subunit is used for determining an operation scheme for an association model, and the association model corresponds to the model to be maintained.

In another embodiment, the apparatus further comprises an update module. The updating module is used for updating the service model word segmentation word bank based on the updating information of the service architecture.

FIG. 8 schematically illustrates a block diagram of a business architecture model maintenance apparatus according to another embodiment of the present disclosure.

As shown in fig. 8, the apparatus 700 may further include a maintenance result output module 810.

The maintenance result output module 810 is configured to output a maintenance result after the maintenance is performed on the model to be maintained and the associated model.

Another aspect of the present disclosure provides a business architecture model maintenance system. FIG. 9 schematically illustrates a block diagram of a business architecture model maintenance system according to an embodiment of the disclosure.

As shown in fig. 9, the business architecture model maintenance system includes: a business model asset management and control system 910, a semantic analysis system 930, and a business model maintenance policy system 950.

The business model asset management and control system 910 is configured to store a business model of a business architecture, send obtained maintenance information to the semantic analysis system 930, and maintain the business model according to a maintenance instruction uploaded by the business model maintenance policy system 950.

The semantic analysis system 930 is configured to process the maintenance information based on the service model participle lexicon to obtain a participle result of the maintenance information.

The business model maintenance policy system 950 is configured to determine a maintenance instruction based on the word segmentation result and the database task model, and send the maintenance instruction to the business model asset management and control system 910.

Specifically, the business model asset management and control system 910 is connected to the semantic analysis system 930, and the semantic analysis system 930 is connected to the business model maintenance policy system 950. The business model maintenance policy system 950 is connected to the business model asset management system 910.

The business model asset management and control system 910 is responsible for receiving and processing the maintenance information, converting the speech to Chinese text locally or remotely if the user inputs the speech, and sending the Chinese text to the semantic analysis system 930. The business model asset management and control system 910 is also responsible for storing the business model of the business architecture and automatically updating the business model according to the database task uploaded by the business model maintenance policy system. The enterprise-level business architecture model comprises an entity model, a process model and a product model. The entity model comprises a business field, a business component, a business object, a business entity and graphic and text description of attributes. The process model comprises a business field, a value flow, an activity, a task component and steps. The product model includes a product line, a product group, a product condition, and a product attribute.

The semantic analysis system 930 is responsible for receiving the chinese text sent by the business model asset management and control system 910 and segmenting the chinese text according to the business model segmentation lexicon and the segmentation policy. The service model word segmentation library comprises operation type word segmentation such as 'modification', 'deletion', 'addition', and the like. The asset class participles are asset type participles such as "business object", "entity", "task group", "task component", "attribute", and the like. The type word segmentation entity is such as 'order taking order' and the like, and the maintenance of the word stock can be updated in real time through the crawler asset management and control system. The word segmentation strategy comprises the following steps: firstly, each word in the input Chinese sentence is matched with the dictionary in sequence, if the word is found in the dictionary, the matching is successful, and a boundary mark is added. For example, user input: deleting the return mark attribute under the return information entity of the order receiving order under the order receiving order business object, wherein the word segmentation result is as follows: delete/order take/business object/order take/return information/entity/order take/return flag/attribute. Then, words which are irrelevant to semantics, such as words, symbols and the like, are removed from the word segmentation result to obtain Chinese word segmentation semantics deletion/order receiving/business object/order receiving/goods returning information/entity/goods returning mark/attribute. Then, the operation class participle and the asset class participle in the Chinese participle word meaning are extracted to obtain a semantic mode, such as deletion/business object/entity/attribute. The segmentation results including the Chinese segmentation semantics and the semantic mode are sent to the business model maintenance policy system 950.

The business model maintenance policy system 950 is responsible for receiving the word segmentation result transmitted from the semantic analysis system 930, analyzing the word segmentation result in combination with the maintenance policy model to obtain a database operation task, and uploading the database operation task to the business model asset management and control system 910. The maintenance strategy model is specially established in the field of business models, and a semantic mode, a maintenance scheme and a database task model are established through expert analysis. For details, reference may be made to relevant parts of the method, which are not described herein again.

In one embodiment, the business model asset management and control system 910 includes a business model query module, a business model maintenance module, a speech recognition module, and a user requirement acquisition module.

The service model query module is connected with the service model maintenance module and the user demand acquisition module. The business model maintenance module is connected with the business model query module. The voice recognition module is connected with the user demand acquisition module. The user demand acquisition module is connected with the service model query module and the voice recognition module.

The business model query module is responsible for querying model information of the business architecture, including querying a product model, a process model and an entity model.

The business model maintenance module is responsible for storing and maintaining a product model, a process model and an entity model, and the maintenance of the model comprises three types of operations of adding, modifying and deleting.

The voice recognition module is responsible for synthesizing Chinese text through the voice information transmitted by the raw user requirement acquisition module. And transmitting the Chinese text result to the user requirement acquisition module.

The user requirement acquisition module is responsible for acquiring user requirements such as maintenance information. The maintenance information may include text information and voice information. If the user inputs the voice, the voice information is transmitted to the voice recognition module, and the Chinese text result fed back by the voice recognition module is received after the voice recognition module recognizes the voice information.

In another embodiment, the semantic segmentation system 930 may include a business model thesaurus module, a business model-based Chinese semantic segmentation strategy module, a Chinese semantic-based segmentation generation module, a business model operation class thesaurus module, a business model instance class thesaurus module, and a business model asset class thesaurus module.

The business model word library module is respectively connected with the word segmentation generation module, the business model operation class word library module, the business model instance class word library module and the business model asset class word library module. The Chinese semantic word segmentation strategy module is connected with the word segmentation generation module.

The business model word library module stores a business model operation class word library, an example class word library and an asset class word library of a business architecture.

And the business model operation class word library module is responsible for updating the operation class word library. The operation class lexicon comprises: "newly added", "modified", "deleted", etc. And updating the word stock according to the habit of the user.

And the business model instance word library module is responsible for updating the instance word library. The instance class thesaurus includes updates to different asset type instances such as "order taking". The crawler can be updated for the business asset management and control system.

And the business model asset class word library module is responsible for updating the asset class word library. The asset class thesaurus comprises updates of different asset type instances of 'business object', 'entity', 'task component', 'product condition'. The crawler can be updated for the business asset management and control system.

The Chinese semantic word segmentation strategy module based on the business model is responsible for creating, verifying and maintaining the word segmentation model strategy.

The Chinese semantic based word segmentation generation module is responsible for carrying out word segmentation on the Chinese text by the word segmentation strategy transmitted by the word bank module of the business model and the Chinese semantic word segmentation strategy module of the business model, and the word segmentation result comprises a semantic mode and Chinese word segmentation semantics.

The business model maintenance policy system 950 includes a business model maintenance rule module, a business model maintenance task generation module, and a maintenance task transmission module. The business model maintenance rule module is connected with the business model maintenance task generation module, and the business model maintenance task generation module is connected with the business model maintenance rule module and the maintenance task sending module.

And the business model maintenance rule module is responsible for storing and maintaining the rule model. The maintenance rule model service model is exclusive in field, and a Chinese semantic template, a maintenance scheme and a database task model are created through expert analysis, and specific contents can refer to relevant parts of the method and are not described again.

And the business model maintenance task generation module is responsible for generating and maintaining database tasks. And according to the Chinese word segmentation result, performing similarity matching on the input semantic mode and the semantic template in the model, and finding out the template with the maximum similarity to the input. And supplementing the variables according to the Chinese word segmentation semantics to obtain a database execution task. The specific process of selecting the semantic template can refer to the method-related part, and is not described herein again.

And the maintenance task sending module is responsible for sending the maintenance task of the service model maintenance information generation module to the service model asset management and control system.

In one embodiment, a method of operating the model maintenance system is described. The service model asset management and control system 910 obtains the user maintenance requirements, such as the maintenance information input by the user, and the semantic word segmentation system 930 performs word segmentation on the text type maintenance information by using the service model word segmentation lexicon and obtains a semantic-based word segmentation mode and a semantic word segmentation result. The business model maintenance policy system 950 formulates policy models between different types of maintenance modes, maintenance schemes, database tasks. By matching the Chinese semantic word segmentation result and the maintenance strategy model, the database operation task is analyzed and uploaded to the business model asset management and control system 910. The business model asset management and control system 910 performs database tasks to complete the automated maintenance of the models.

Specifically, the operation method of the model maintenance system may include the following operations.

Firstly, the business model asset management and control system 910 obtains user requirements, which may be a chinese text or a speech input, if the user inputs a speech, the speech is converted into a text by the speech recognition module, and then the chinese text obtained by the speech recognition is uploaded to the semantic analysis system 930.

Then, the semantic analysis system 930 receives the Chinese sentence and performs word segmentation on the Chinese sentence according to the business model lexicon and the word segmentation strategy. The word segmentation result comprises a semantic mode and Chinese word segmentation semantics. The segmentation results are then uploaded to the business model maintenance policy system 950.

Then, the business model maintenance policy system 950 receives the word segmentation result, generates a database maintenance task according to the model rule, and sends the maintenance task to the business model asset management and control system.

Then, the database maintenance task received by the business model asset management and control system 910 is executed, and the execution result is fed back to the user.

The operation method of the business model asset management system 910 is as follows. The business model module stores business models including a process model, a product model and an entity model.

Firstly, a user demand module acquires maintenance information, and if the maintenance information comprises voice information input by a user, a voice recognition module is called to convert the voice into a Chinese text. The voice recognition module converts the received voice into a Chinese text and feeds the Chinese text back to the user demand module.

And then, the service model updating module updates data according to the tasks fed back by the service model maintenance strategy system feedback module and displays the updated result to the user.

The method of operation of the semantic analysis system may be as follows.

Firstly, the business model word library module is responsible for maintaining an operation class word library, an asset class word library and an instance class word library, specifically, a crawler technology can be adopted to crawl a business model asset management and control system, and the word library is updated in real time according to crawler results. And uploading the latest word bank to a Chinese word segmentation generation module based on semantics.

Then, the Chinese semantic word segmentation strategy module is responsible for creating and maintaining the word segmentation strategy. And the latest strategy is sent to a Chinese word segmentation generation module based on the semantic meaning.

And then, the Chinese word segmentation generation module based on the semantics generates word segmentation results according to the Chinese text, the business model word bank and the word segmentation strategy, wherein the word segmentation results comprise a semantic mode and Chinese word segmentation semantics. And then sending the word segmentation result to a service model maintenance strategy system.

The method of operation of the business model maintenance policy system may be as follows.

Firstly, the business model maintenance rule module is responsible for training, verifying and maintaining the model. And sending the trained model to a service model maintenance information generation module.

Then, the business model maintenance information generation module calculates the similarity of the Chinese semantic templates according to the semantic recognition result, selects the template with the highest similarity, and completes the corresponding variables. And outputting the maintenance task corresponding to the maintenance information according to the maintenance rule model.

And then, the information sending module sends the maintenance task to the service model asset management and control system.

According to the model maintenance system provided by the embodiment of the disclosure, through the operation method, automatic maintenance of the model can be realized, maintenance efficiency is improved, and maintenance difficulty is reduced.

According to the model maintenance system provided by the embodiment of the disclosure, a service model asset management and control system is used for acquiring user maintenance requirements, and a semantic word segmentation system is used for segmenting maintenance requirement information by using a service model word segmentation word bank and obtaining a semantic word segmentation mode and a semantic word segmentation result based on semantics. The business model maintenance strategy system makes strategy models among different types of maintenance modes, maintenance schemes and database tasks. And analyzing and obtaining a database operation task to be uploaded to a business model asset management and control system by matching the semantic word segmentation result and the maintenance strategy model. And the asset management and control system executes database tasks and completes the automatic maintenance of the model without manual operation of a user.

It should be noted that the implementation, solved technical problems, implemented functions, and achieved technical effects of each module/unit and the like in the apparatus part embodiment are respectively the same as or similar to the implementation, solved technical problems, implemented functions, and achieved technical effects of each corresponding step in the method part embodiment, and are not described in detail herein.

Any of the modules, units, or at least part of the functionality of any of them according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules and units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, units according to the embodiments of the present disclosure may be implemented at least partially as a hardware circuit, 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 a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by any other reasonable means of hardware or firmware by integrating or packaging the circuits, or in any one of three implementations of software, hardware and firmware, or in any suitable combination of any of them. Alternatively, one or more of the modules, units according to embodiments of the present disclosure may be implemented at least partly as computer program modules, which, when executed, may perform the respective functions.

For example, any plurality of the maintenance information obtaining module 710, the maintenance instruction determining module 730, and the maintenance module 750 may be combined and implemented in one module, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the maintenance information obtaining module 710, the maintenance instruction determining module 730, and the maintenance module 750 may be implemented at least partially as a hardware circuit, 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 a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or may be implemented by any one of three implementations of software, hardware, and firmware, or any suitable combination of any of them. Alternatively, at least one of the maintenance information obtaining module 710, the maintenance instruction determining module 730 and the maintenance module 750 may be at least partially implemented as a computer program module, which when executed, may perform a corresponding function.

One aspect of the present disclosure provides an electronic device. FIG. 10 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure. The electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 10, an electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1008 into a Random Access Memory (RAM) 1003. Processor 1001 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 1001 may also include onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the present disclosure.

In the RAM 1003, various programs and data necessary for the operation of the electronic apparatus 1000 are stored. The processor 1001, the ROM 1002, and the RAM 1003 are communicatively connected to each other by a bus 1004. The processor 1001 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 1002 and/or the RAM 1003. Note that the program may also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in one or more memories.

Electronic device 1000 may also include an input/output (I/O) interface 1005, the input/output (I/O) interface 1005 also being connected to bus 1004, according to an embodiment of the present disclosure. Electronic device 1000 may also include one or more of the following components connected to I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.

According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. The computer program performs the above-described functions defined in the system of the embodiment of the present disclosure when executed by the processor 1001. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 1002 and/or the RAM 1003 described above and/or one or more memories other than the ROM 1002 and the RAM 1003.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. These examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. A service architecture model maintenance method executed by a server side comprises the following steps:

obtaining maintenance information, wherein the maintenance information comprises a model to be maintained;

determining a maintenance instruction corresponding to the maintenance information, wherein the maintenance instruction comprises a first maintenance instruction for the model to be maintained and a second maintenance instruction for an associated model, and the associated model is a model related to the model to be maintained in a business architecture; and

and responding to the first maintenance instruction and the second maintenance instruction, and maintaining the model to be maintained and the correlation model.

2. The method of claim 1, wherein the determining a maintenance instruction corresponding to the maintenance information comprises: with respect to the maintenance information of the text type,

performing word segmentation on the maintenance information of the text type based on a service model word segmentation word bank to obtain a word segmentation result, wherein the word segmentation result comprises at least one of operation class word segmentation, asset class word segmentation and semantic mode;

determining an operation scheme based on the word segmentation result; and

and determining a maintenance instruction based on the operation scheme and a database task model, wherein the database task model comprises a mapping relation between the operation scheme and the maintenance instruction.

3. The method of claim 2, wherein:

the service model word segmentation word bank comprises: at least one of a business model operation class word library, a business model asset class word library and a business model instance class word library;

the word segmentation is performed on the maintenance information of the text type based on the service model word segmentation word bank, and the word segmentation result is obtained by the method comprising the following steps:

matching the words in the maintenance information with the operation class word segmentation word library of the service model respectively to obtain operation class words; respectively matching the words in the maintenance information with the asset class word banks of the service models to obtain asset class words; matching the words in the maintenance information with the example word library of the service model respectively to obtain example words; and

determining a semantic schema based on the operation class terms and the asset class terms.

4. The method of claim 2, wherein the determining an operational scheme based on the word segmentation results comprises:

determining a current semantic template based on the similarity between the semantic mode and a semantic template in a maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable; and

determining an operating recipe for the model to be maintained and the associated model based on the operation class terms, the asset class terms, and the current semantic template.

5. The method of claim 4, wherein the similarity comprises a structural similarity and a semantic similarity, and the sum of the weights of the structural similarity and the semantic similarity is 100%.

6. The method of claim 5, wherein the structural similarity comprises: at least one of the similarity of word shape, the similarity of word order and the similarity of sentence length.

7. The method of claim 4, wherein the determining an operational scenario for the model to be maintained and the associated model based on the operation class terms, the asset class terms, and the current semantic template comprises:

filling the current semantic template with the operation words and the asset words to obtain an operation scheme for the model to be maintained; and

determining an operating recipe for the association model, the association model corresponding to the model to be maintained.

8. The method of claim 2, further comprising: after obtaining the maintenance information, for voice-type maintenance information,

and obtaining a voice recognition result aiming at the maintenance information of the voice type so as to obtain the maintenance information of the text type corresponding to the maintenance information of the voice type.

9. The method of claim 2, further comprising:

and updating the business model word segmentation word bank based on the updating information of the business architecture.

10. The method of claim 1, further comprising: after maintenance of the model to be maintained and the associated model,

and outputting a maintenance result.

11. A business architecture model maintenance apparatus, comprising:

the maintenance information acquisition module is used for acquiring maintenance information, and the maintenance information comprises a model to be maintained;

a maintenance instruction determining module, configured to determine a maintenance instruction corresponding to the maintenance information, where the maintenance instruction includes a first maintenance instruction for the model to be maintained and a second maintenance instruction for an association model, and the association model is a model related to the model to be maintained in a service architecture; and

and the maintenance module is used for responding to the first maintenance instruction and the second maintenance instruction and maintaining the model to be maintained and the correlation model.

12. The apparatus of claim 11, wherein the maintenance order determination module comprises:

the word segmentation submodule is used for segmenting the maintenance information of the text type based on a business model word segmentation word bank to obtain a word segmentation result, and the word segmentation result comprises at least one of operation class word segmentation, asset class word segmentation and a semantic mode;

a scheme determination submodule for determining an operation scheme based on the word segmentation result; and

and the instruction determining submodule is used for determining a maintenance instruction based on the operation scheme and the database task model, wherein the database task model comprises a mapping relation between the operation scheme and the maintenance instruction.

13. The apparatus of claim 12, wherein the scheme determination submodule comprises:

the semantic template determining unit is used for determining a current semantic template based on the similarity between the semantic mode and a semantic template in the maintenance strategy model, wherein the semantic template comprises an operation variable and an asset variable; and

and the scheme determining unit is used for determining the operation scheme aiming at the model to be maintained and the associated model based on the operation class words, the asset class words and the current semantic template.

14. The apparatus of claim 12, further comprising:

and the updating module is used for updating the business model word segmentation word bank based on the updating information of the business architecture.

15. The apparatus of claim 11, further comprising:

and the maintenance result output module is used for outputting a maintenance result after the model to be maintained and the correlation model are maintained.

16. A business architecture model maintenance system, comprising:

the business model asset management and control system is used for storing a business model of a business architecture, sending the obtained maintenance information to the semantic analysis system and maintaining the business model according to the maintenance instruction uploaded by the business model maintenance strategy system;

the semantic analysis system is used for processing the maintenance information based on the service model word segmentation word bank so as to obtain a word segmentation result of the maintenance information; and

and the business model maintenance strategy system is used for determining a maintenance instruction based on the word segmentation result and the database task model and sending the maintenance instruction to the business model asset management and control system.

17. An electronic device, comprising:

one or more processors;

a storage device for storing executable instructions which, when executed by the processor, implement a method according to any one of claims 1 to 10.

18. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, implement a method according to any one of claims 1 to 10.