CN111062600A - Model evaluation method, system, electronic device, and computer-readable storage medium - Google Patents
Model evaluation method, system, electronic device, and computer-readable storage medium Download PDFInfo
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- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
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- G—PHYSICS
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- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G06Q10/06395—Quality analysis or management
Abstract
The present disclosure provides a model evaluation method, comprising: constructing a basic database according to the business architecture description models of the plurality of stocks, wherein the basic database comprises quality analysis information of the business architecture description model of each stock; acquiring a description model of a newly added service architecture to be evaluated, wherein the description model of the newly added service architecture comprises a plurality of description entries for describing the description model of the newly added service architecture; and based on the quality analysis information in the basic database, performing quality evaluation on the description items of the newly added service architecture description model. The present disclosure also provides a model evaluation system, an electronic device, and a computer-readable storage medium.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and more particularly, to a model evaluation method, a model evaluation system, an electronic device, and a computer-readable storage medium.
Background
The structural business architecture description realizes the unified presentation of the architecture, business and system of enterprise production and operation through the top-down description. Therefore, the accuracy of the business architecture description model is of great significance for understanding the production and operation conditions of the enterprise. With the continuous development of large-scale enterprise business, the business architecture description model also needs to be synchronously and iteratively promoted. In the related art, the iterative upgrade work is generally completed by a business requirement department, and since the specific executive staff has different understanding levels on the business architecture and the production operation, the business architecture management department needs to evaluate the maturity of the business architecture modeling result of the iterative upgrade and the business architecture maturity after iteration. At present, for a business architecture description model, there is no quantitative evaluation method, and generally, only qualitative evaluation can be performed, for example, multiple experts are used to evaluate a newly added business architecture description model, but the inventor finds that the evaluation method requires high time and labor cost, and the evaluation result highly depends on the experience of an evaluator.
Disclosure of Invention
In view of the above, the present disclosure provides a model evaluation method, a model evaluation system, an electronic device, and a computer-readable storage medium.
One aspect of the present disclosure provides a model evaluation method, including: constructing a basic database according to a plurality of stock business architecture description models, wherein the basic database comprises quality analysis information of each stock business architecture description model; acquiring a description model of a newly added service architecture to be evaluated, wherein the description model of the newly added service architecture comprises a plurality of description entries for describing the description model of the newly added service architecture; and based on the quality analysis information in the basic database, performing quality evaluation on the description items of the newly added service architecture description model.
According to an embodiment of the present disclosure, the quality analysis information of the business architecture description model of each stock includes at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
According to an embodiment of the present disclosure, the quality evaluation of the description entry of the newly added service architecture description model based on the quality analysis information in the basic database includes: evaluating the description items of the newly added service architecture description model based on the mathematical statistic information and/or the incidence relation analysis information, and determining whether the description items of the newly added service architecture description model meet the screening condition; and screening out the description items which do not meet the screening condition to obtain the description items which meet the screening condition.
According to an embodiment of the present disclosure, the method further includes: after obtaining the description items meeting the screening conditions, performing association rule mining on the business architecture description model of each stock and the newly added business architecture description model; and based on the correlation rule mining result, performing secondary screening on the description items meeting the screening condition through abnormality detection to screen out abnormal description items.
According to an embodiment of the present disclosure, the method further includes: performing cluster analysis on the newly added service architecture description model and the service architecture description model stored in the basic database by using a cluster analysis method; determining the degree of association between the newly added service architecture description model and the service architecture description model of the stock in the basic database based on the clustering analysis result; and determining the quality of the newly added service architecture description model based on the quality of the stock service architecture description model of which the association degree with the newly added service architecture description model meets a preset threshold value.
According to an embodiment of the present disclosure, the method further includes: after the description items meeting the screening condition are obtained or abnormal description items are screened out, performing semantic analysis on the residual description items which are not analyzed in the newly added service architecture description model; and screening out the remaining description entries which do not satisfy the semantic analysis condition.
According to an embodiment of the present disclosure, the method further includes: and after the quality evaluation is carried out on the description items of the newly added service architecture description model, generating a visual chart of the quality evaluation result of the newly added service architecture description model.
Another aspect of the present disclosure provides a model evaluation system, including: the system comprises a construction module, a quality analysis module and a quality analysis module, wherein the construction module is used for constructing a basic database according to a plurality of stock business architecture description models, and the basic database comprises quality analysis information of each stock business architecture description model; the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a newly added service architecture description model to be evaluated, and the newly added service architecture description model comprises a plurality of description entries for describing the newly added service architecture description model; and the evaluation module is used for evaluating the quality of the description items of the newly added service architecture description model based on the quality analysis information in the basic database.
According to an embodiment of the present disclosure, the quality analysis information of the business architecture description model of each stock includes at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
According to an embodiment of the present disclosure, the above evaluation module includes: an evaluation unit, configured to evaluate the description entry of the newly added service architecture description model based on the mathematical statistics information and/or the association analysis information, and determine whether the description entry of the newly added service architecture description model satisfies a screening condition; and the screening unit is used for screening the description items which do not meet the screening conditions to obtain the description items which meet the screening conditions.
According to an embodiment of the present disclosure, the system described above further includes: the data mining analysis module is used for mining the association rule of the business architecture description model of each stock and the newly added business architecture description model after obtaining the description items meeting the screening condition; the screening unit is further configured to perform secondary screening on the description entries meeting the screening condition through abnormality detection based on the association rule mining result, and screen out abnormal description entries.
According to an embodiment of the present disclosure, the data mining analysis module is further configured to: using a cluster analysis system to perform cluster analysis on the newly added service architecture description model and the service architecture description model stored in the basic database; determining the degree of association between the newly added service architecture description model and the service architecture description model of the stock in the basic database based on the clustering analysis result; and determining the quality of the newly added service architecture description model based on the quality of the stock service architecture description model of which the association degree with the newly added service architecture description model meets a preset threshold value.
According to an embodiment of the present disclosure, the system described above further includes: the semantic analysis module is used for performing semantic analysis on the residual description items which are not analyzed in the newly added service architecture description model after obtaining the description items meeting the screening condition or after screening the abnormal description items; and the screening unit is also used for screening out the residual description items which do not meet the semantic analysis condition.
According to an embodiment of the present disclosure, the system further includes a reporting module, further configured to generate a visual chart of a quality evaluation result of the newly added service architecture description model after performing quality evaluation on the description entries of the newly added service architecture description model.
Another aspect of the present disclosure provides an electronic device including: one or more processors; a memory for storing one or more instructions, wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to 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.
According to the embodiment of the disclosure, the basic database is constructed according to the business architecture description models of a plurality of stocks, and the quality evaluation is performed on the description entries of the newly added business architecture description model based on the quality analysis information of the business architecture description model of each stock in the basic database, so that the quality evaluation can be automatically performed on the description entries of the newly added business architecture description model according to the quality analysis information of the business architecture description model of each stock in the basic database, the technical problems of high dependence on experts and incapability of quantitative evaluation are at least partially solved, and the evaluation cost and quality can meet the requirements of business development and system iteration.
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 an exemplary system architecture to which the model evaluation methods and systems may be applied, according to an embodiment of the disclosure;
FIG. 2 schematically illustrates a flow diagram of a model evaluation method according to an embodiment of the present disclosure;
FIG. 3 schematically shows a schematic diagram of a business architecture description model according to an embodiment of the present disclosure;
FIG. 4 schematically shows a schematic view of a product model according to an embodiment of the disclosure;
FIG. 5 schematically shows a schematic diagram of a solid model according to an embodiment of the disclosure;
fig. 6 schematically shows a flowchart for performing quality evaluation on a description entry of a newly added service architecture description model according to an embodiment of the present disclosure;
fig. 7 schematically shows a flowchart for performing quality evaluation on a description entry of a newly added service architecture description model according to another embodiment of the present disclosure;
fig. 8 schematically shows a flowchart for performing quality evaluation on a description entry of a new service architecture description model according to another embodiment of the present disclosure;
fig. 9 schematically shows a flowchart for performing quality evaluation on a description entry of a newly added service architecture description model according to another embodiment of the present disclosure;
fig. 10 schematically illustrates a flow chart of quality assessment of a new service architecture description model according to another embodiment of the present disclosure;
FIG. 11 schematically shows a block diagram of a model evaluation system according to an embodiment of the present disclosure; and
FIG. 12 schematically illustrates a block diagram of a computer system suitable for implementing the model evaluation method described above, in accordance with an embodiment of the present 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.).
An embodiment of the present disclosure provides a model evaluation method, including: constructing a basic database according to the business architecture description models of the plurality of stocks, wherein the basic database comprises quality analysis information of the business architecture description model of each stock; acquiring a description model of a newly added service architecture to be evaluated, wherein the description model of the newly added service architecture comprises a plurality of description entries for describing the description model of the newly added service architecture; and based on the quality analysis information in the basic database, performing quality evaluation on the description items of the newly added service architecture description model.
FIG. 1 schematically illustrates an exemplary system architecture to which the model evaluation methods and systems may be applied, according to an embodiment of the disclosure. It should be noted that fig. 1 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. 1, the system architecture 100 according to the embodiment may include a terminal device 101 used by a business architecture modeling person, a terminal device 102 used by a business architecture evaluating person, a quality evaluating server 103, a business architecture description model server 104 storing inventory, and other servers 105. The terminal devices 101 and 102, and the servers 103, 104 and 105 may be communicatively coupled via wired and/or wireless communication links.
The business architecture modeler may use the terminal device 101 to build a new business architecture description model for the enterprise. The service architecture evaluator may initiate an evaluation request of the new service architecture description model by using the terminal device 102, and the quality evaluation server 103 may respond to the evaluation request. The quality evaluation server 103 may obtain a plurality of stock business architecture description models from the storage business architecture description model server 104 in advance, and calculate and generate a basic database for business architecture quality analysis according to the plurality of stock business architecture description models and according to a statistical and data mining method, wherein the database includes mathematical statistical information, association analysis information, clustering information and semantic analysis information of each component of the model. According to embodiments of the present disclosure, model components may include, for example, domains, activities, tasks, entities, products, and so forth.
The servers 103-105 may be servers that provide various services, such as a back-office management server (for example only) that provides support for web sites browsed by users using the terminal devices 101 and 102. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the model evaluation method provided by the embodiment of the present disclosure may be generally executed by the server 103. Accordingly, the model evaluation system provided by the embodiments of the present disclosure may be generally disposed in the server 103. The model evaluation method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 103 and is capable of communicating with the terminal devices 101 and 102 and/or the server 103, and the like. Accordingly, the model evaluation system provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 103 and capable of communicating with the terminal devices 101 and 102 and/or the server 103.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
FIG. 2 schematically shows a flow diagram of a model evaluation method according to an embodiment of the disclosure.
As shown in fig. 2, the method includes operations S210 to S230.
In operation S210, a base database is constructed according to a plurality of inventory business architecture description models, wherein the base database includes quality analysis information of each inventory business architecture description model.
According to an embodiment of the present disclosure, the business architecture description model of the inventory may be a business architecture description model that has been already built and has better quality after quality evaluation. The business architecture description model of the stock can also be a template model of the business architecture description model specially used for quality evaluation.
According to an embodiment of the present disclosure, the quality analysis information of the business architecture description model of each stock may include at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
In operation S220, a description model of the newly added service architecture to be evaluated is obtained, where the description model of the newly added service architecture includes a plurality of description entries for describing the description model of the newly added service architecture.
According to an embodiment of the present disclosure, the newly added business architecture description model may be an enterprise business model newly built by business architecture modelers. The description entries for describing the description model of the new service architecture may be description entries about each constituent part of the description model of the new service architecture.
In operation S230, quality evaluation is performed on the description entries of the newly added service architecture description model based on the quality analysis information in the basic database.
FIG. 3 schematically shows a schematic diagram of a business architecture description model according to an embodiment of the disclosure.
According to the embodiment of the disclosure, the description of the business architecture is a top-down structural description method of the enterprise business, the business architecture description model is obtained by performing top-down structural description on the enterprise business, and the business architecture description model comprises description items for describing the architecture, the business and the system of the enterprise production and operation.
As shown in FIG. 3, the description entries of business architecture description model 300 may include, for example, textual descriptions and associations of business architecture flow models 301, product models 302, and entity models 303 used in the enterprise. According to an embodiment of the present disclosure, the business architecture description model 300 may be referred to for the composition of the newly added business architecture description model and the stock business architecture description model.
According to an embodiment of the present disclosure, the process model 301 may refer to that services in different service fields are divided based on planning, executing, and monitoring value streams of the services, each value stream is divided into different activities, the activities are divided into tasks, and the tasks are divided into process descriptions after steps according to service rules and conditions, for example, the process model 301 may include five levels, service fields-value streams-activities-tasks-steps.
Taking banking as an example, in the process model 301, the business fields generally include but are not limited to: personal deposits, personal accounts, credit cards, personal loans, and the like. Value streams generally include, but are not limited to: business planning, business preparation, servicing customers, etc. Activities generally include, but are not limited to: making management system, issuing credit card, drawing credit card fund, returning credit card arrears, etc. Tasks generally include, but are not limited to: identifying individual customers, monitoring real-time fraud risk, accepting credit card fund withdrawal applications, settling foreign currencies, and the like.
According to an embodiment of the present disclosure, specifically, taking a credit card as an example, the architecture flow model task of the inventory may be as shown in table 1.
TABLE 1
According to the embodiment of the present disclosure, the description entry of the architecture flow model task of one newly added service architecture description model related to the above inventory entries may be as shown in table 2. The architecture flow model task shown in table 2 may be a quality-qualified task.
TABLE 2
According to the embodiment of the disclosure, on the contrary, if the description entry of the architecture flow model task of the newly added business architecture description model is shown in table 3, the architecture flow model task can be considered as a task with unqualified quality.
TABLE 3
According to an embodiment of the present disclosure, for the description entries in table 3, it is possible to identify by using a data mining module: the range description includes public content which is not included in the credit card service architecture model, such as an enterprise authorized amount, and the associated products are independent of the field of the credit card service.
According to an embodiment of the present disclosure, for the description entry in table 3, it may be identified by the semantic analysis module: the description of public and personal quota is mixed in the definition.
FIG. 4 schematically shows a schematic diagram of a product model according to an embodiment of the disclosure.
As shown in FIG. 4, in the product model 302, there may be a set of standard structures defining the products of the enterprise, including, for example, product lines, product groups, base products, vendable products, and associations between products, according to embodiments of the present disclosure.
Taking banking as an example, the product model 302 generally includes, but is not limited to: debit cards, credit cards, quasi-credit cards, international debit cards, and the like.
FIG. 5 schematically shows a schematic diagram of a solid model according to an embodiment of the disclosure.
As shown in fig. 5, in the entity model 303, the service content of each service object (for example, the service object 1 and the service object 2) is recorded, and each service object includes a core entity, a life cycle (status of the core entity), a subordinate entity (describing attribute information of the core entity), an association relationship between the service objects, and a constraint condition.
Taking banking as an example, the business objects of the entity model 303 generally include, but are not limited to: participant information, participant life cycles, account information, media information, and the like.
In addition, the business architecture description model 300 may also include one-to-one or one-to-many association relationships between the various hierarchical components in the above business architecture process model 301, product model 302, and entity model 303.
According to the embodiment of the disclosure, the newly added business architecture description model can be an abstract presentation of an architecture, a business and a system aiming at enterprise production and operation, and generally comprises a large number of description entries for describing the architecture, the business and the system, and if the description entries are evaluated by experts or other evaluators, the model is not only time-consuming and labor-consuming, but also depends excessively on the experience of the experts or the evaluators. According to the embodiment of the disclosure, the basic database is constructed according to the business architecture description models of a plurality of stocks, and the quality evaluation is performed on the description entries of the newly added business architecture description model based on the quality analysis information of the business architecture description model of each stock in the basic database, so that the quality evaluation can be automatically performed on the description entries of the newly added business architecture description model according to the quality analysis information of the business architecture description model of each stock in the basic database, the technical problems of high dependence on experts and incapability of quantitative evaluation are at least partially solved, and the evaluation cost and quality can meet the requirements of business development and system iteration.
The method shown in fig. 2 is further described with reference to fig. 6-10 in conjunction with specific embodiments.
Fig. 6 schematically shows a flowchart for performing quality evaluation on a description entry of a new service architecture description model according to an embodiment of the present disclosure.
As shown in fig. 6, the quality evaluation of the description entry of the newly added service architecture description model based on the quality analysis information in the basic database includes operations S610 to S620.
In operation S610, the description entries of the newly added service architecture description model are evaluated based on the mathematical statistics information and/or the association analysis information, and it is determined whether the description entries of the newly added service architecture description model satisfy the screening condition.
According to an embodiment of the present disclosure, the mathematical statistic information may be, for example, the number of words normally describing the entry, and the association analysis information may be, for example, an association between different models. For the entry with the number of words only including a few words in the description model of the newly added service architecture, the isolated task description entry which is not related to other tasks and the entry without the related information between different models can be regarded as the description entry which does not satisfy the screening condition.
In operation S620, description entries that do not satisfy the filtering condition are filtered out, resulting in description entries that satisfy the filtering condition.
According to the embodiment of the disclosure, for example, the entry with the number of words being only a few words, the isolated task description entry without relationship with other tasks, and the entry without association information between different models can be screened out. The description entries that do not satisfy the screening condition may be classified with the description entries that satisfy the screening condition, or the description entries that do not satisfy the screening condition may be directly deleted.
Fig. 7 schematically shows a flowchart for performing quality evaluation on a description entry of a new service architecture description model according to another embodiment of the present disclosure.
As shown in fig. 7, in this embodiment, in addition to operations S610 to S620, performing quality evaluation on the description entry of the new service architecture description model may further include operations S710 to S720.
In operation S710, after the description entries satisfying the screening condition are obtained, association rule mining is performed on the service architecture description model and the newly added service architecture description model for each inventory.
In operation S720, description entries satisfying the filtering condition are filtered again through anomaly detection based on the association rule mining result, and the anomalous description entries are filtered out.
According to the embodiment of the disclosure, the association rule mining can be performed on the stock business architecture description model and the newly added business architecture description model by using the big data technology principle, and the abnormal description items are screened by abnormal detection.
Fig. 8 schematically shows a flowchart for performing quality evaluation on a description entry of a new service architecture description model according to another embodiment of the present disclosure.
As shown in fig. 8, in this embodiment, in addition to operations S610 to S620 and S710 to S720, the quality evaluation of the description entry of the new service architecture description model may further include operations S810 to S830.
In operation S810, cluster analysis is performed on the newly added service architecture description model and the service architecture description model stored in the basic database using a cluster analysis method.
In operation S820, a degree of association between the newly added service architecture description model and the service architecture description model of the inventory in the basic database is determined based on the cluster analysis result.
In operation S830, the quality of the newly added service architecture description model is determined based on the quality of the stock service architecture description model whose association degree with the newly added service architecture description model satisfies a preset threshold.
According to the embodiment of the disclosure, the newly added service architecture description models can be grouped by using a cluster analysis method, and the association degree and quality level between the incremental newly added service architecture description models and the service architecture description models stored in the basic database can be judged through the above analysis mode
According to the embodiment of the disclosure, the quality deviation degree of the incremental newly-added business architecture description model and the business architecture description model of the stock in the basic database, the grading score of the model, the statistic data of the stock modeling result and other numerical values can be output, the evaluation efficiency is improved, and the labor cost is reduced.
Fig. 9 schematically shows a flowchart for performing quality evaluation on a description entry of a new service architecture description model according to another embodiment of the present disclosure.
As shown in fig. 9, the quality evaluation of the description entry of the new service architecture description model includes operations S910 to S920.
In operation S910, after obtaining the description entries satisfying the screening condition, or after screening out the abnormal description entries, performing semantic analysis on the remaining description entries that are not analyzed in the newly added service architecture description model.
In operation S920, the remaining description entries that do not satisfy the semantic analysis condition are filtered out.
According to the embodiment of the disclosure, whether the incidence relation set in the newly added service architecture description model is related to the language description in the newly added service architecture description model can be analyzed through a semantic analysis method. In addition, through a semantic analysis method, whether the purpose, definition and range of the service described in the description item of the newly added service architecture description model are related to the service field to which the description item of the newly added service architecture description model belongs can be analyzed. In the case of no correlation, the description entry may be marked as a non-conforming entry or as a suspect entry.
According to the embodiment of the disclosure, the screening out of the remaining description entries which do not satisfy the semantic analysis condition may be to classify the remaining description entries which do not satisfy the semantic analysis condition with the remaining description entries which satisfy the semantic analysis condition, or to delete the remaining description entries which do not satisfy the semantic analysis condition.
According to an embodiment of the present disclosure, the newly added business architecture description model description entry may be a description entry that updates and modifies an existing business architecture model component. For each description entry that modifies or updates the business architecture description model, the present disclosure may score the description entry for evaluation.
According to the embodiment of the disclosure, after the quality evaluation is performed on the description entries of the newly added service architecture description model, a visual chart of the quality evaluation result of the newly added service architecture description model can be generated.
According to the embodiment of the disclosure, the processed data of the new service architecture description model can be generated into a visual chart for the reference of a user according to the input data format. The effects of automatic evaluation and visual display are achieved, meanwhile, a user can find the problems existing in the newly added service architecture description model, and the working efficiency is improved.
Fig. 10 schematically shows a flowchart of quality evaluation of a new service architecture description model according to another embodiment of the present disclosure.
As shown in fig. 10, the method includes operations S1010 to S1060.
In operation S1010, it is determined whether the quality parameter needs to be adjusted according to actual needs. Taking financial business as an example, the quality parameters may be: word number intervals, the similarity degree of the association relation between the word number intervals and the original domain architecture process model, the similarity degree of the entity model associated with the original domain process model and the like.
In operation S1020, the new service architecture description model data is imported into the database.
In operation S1030, low-quality entry data that may be regarded as quality failure is excluded, and a description entry of the newly added service architecture description model whose quality is to be further evaluated is preliminarily screened out.
In operation S1040, the association between the newly added service architecture description model and the stock service architecture description model is mined, abnormal entries are screened, and the overall quality level of the entry set is determined.
In operation S1050, a semantic analysis and screening engine is used to determine whether the language description in the newly added service architecture description model is related to the service domain and conforms to the correlation between the described models.
In operation S1060, a data quality report of the current incremental model is output.
The method and the device can solve the problems that the service architecture quality evaluation process is highly dependent on experts, cannot be evaluated quantitatively, consumes time and labor cost and the like. The cost and quality of quality evaluation can be reduced, so that the service architecture quality evaluation meets the requirements of high-speed development of various services and frequent iteration of information system codes of the current large-scale enterprise. Meanwhile, the accuracy of the model evaluation system can be improved by data mining and semantic analysis data accumulation, and quantitative analysis results are provided for the enterprise to evaluate the quality of the enterprise business architecture description model on the whole.
According to the embodiment of the disclosure, a model evaluation system for evaluating the maturity of the business architecture description model is also provided, and the model evaluation system can be used for post-evaluation work of the business architecture description model and used for evaluating the accuracy and the maturity of the enterprise business architecture description model.
FIG. 11 schematically shows a block diagram of a model evaluation system according to an embodiment of the disclosure.
As shown in FIG. 11, model evaluation system 1100 includes a build module 1110, an obtain module 1120, and an evaluate module 1130.
The building module 1110 is configured to build a base database according to the business architecture description models of the plurality of inventory quantities, where the base database includes quality analysis information of the business architecture description model of each inventory quantity.
The obtaining module 1120 is configured to obtain a new service architecture description model to be evaluated, where the new service architecture description model includes a plurality of description entries for describing the new service architecture description model.
The evaluation module 1130 is configured to perform quality evaluation on the description entry of the newly added service architecture description model based on the quality analysis information in the basic database.
According to an embodiment of the present disclosure, the quality analysis information of the business architecture description model of each stock includes at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
The evaluation module 1130 includes an evaluation unit and a culling unit according to embodiments of the present disclosure.
The evaluation unit is used for evaluating the description items of the newly added service architecture description model based on the mathematical statistic information and/or the incidence relation analysis information, and determining whether the description items of the newly added service architecture description model meet the screening condition.
The screening unit is used for screening the description items which do not meet the screening conditions to obtain the description items which meet the screening conditions.
According to the embodiment of the present disclosure, the model evaluation system 1100 further includes a data mining analysis module, configured to perform association rule mining on the service architecture description model and the newly added service architecture description model of each stock after obtaining the description entries meeting the screening condition.
According to the embodiment of the disclosure, the screening unit is further configured to screen again the description entries satisfying the screening condition through the abnormality detection based on the correlation rule mining result, and screen out the abnormal description entries.
According to an embodiment of the present disclosure, the data mining analysis module is further configured to: using a cluster analysis system to perform cluster analysis on the newly added service architecture description model and the service architecture description model of the stock in the basic database; determining the association degree between the newly added service architecture description model and the service architecture description model of the stock in the basic database based on the clustering analysis result; and determining the quality of the newly added service architecture description model based on the quality of the stock service architecture description model of which the association degree with the newly added service architecture description model meets a preset threshold value.
According to the embodiment of the present disclosure, the model evaluation system 1100 further includes a semantic analysis module, configured to perform semantic analysis on remaining description entries that are not analyzed in the newly added service architecture description model after obtaining the description entries that meet the screening condition or after screening out the abnormal description entries.
According to an embodiment of the present disclosure, the screening unit is further configured to screen out remaining description entries that do not satisfy the semantic analysis condition.
According to the embodiment of the present disclosure, the model evaluation system 1100 further includes a reporting module, and is further configured to generate a visual chart of a quality evaluation result of the newly added service architecture description model after performing quality evaluation on the description entries of the newly added service architecture description model.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-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, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part 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 in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
For example, any number of the building module 1110, the obtaining module 1120, and the evaluating module 1130 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the building module 1110, the obtaining module 1120, and the evaluating module 1130 may be implemented at least in part 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 in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware. Alternatively, at least one of the building module 1110, the obtaining module 1120, and the evaluating module 1130 may be implemented at least in part as a computer program module, which when executed, may perform a corresponding function.
It should be noted that, the model evaluation system part in the embodiment of the present disclosure corresponds to the model evaluation method part in the embodiment of the present disclosure, and the description of the model evaluation system part specifically refers to the model evaluation method part, which is not described herein again.
According to an embodiment of the present disclosure, there is also provided an electronic apparatus including: one or more processors; a memory for storing one or more instructions, wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to implement the method described above.
FIG. 12 schematically illustrates a block diagram of a computer system suitable for implementing the above-described method, in accordance with an embodiment of the present disclosure. The computer system illustrated in FIG. 12 is only one example and should not impose any limitations on the scope of use or functionality of embodiments of the disclosure.
As shown in fig. 12, a computer system 1200 according to an embodiment of the present disclosure includes a processor 1201, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1202 or a program loaded from a storage section 1208 into a Random Access Memory (RAM) 1203. The processor 1201 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 1201 may also include on-board memory for caching purposes. The processor 1201 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the present disclosure.
In the RAM 1203, various programs and data necessary for the operation of the system 1200 are stored. The processor 1201, the ROM1202, and the RAM 1203 are connected to each other by a bus 1204. The processor 1201 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM1202 and/or the RAM 1203. Note that the programs may also be stored in one or more memories other than the ROM1202 and the RAM 1203. The processor 1201 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
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 section 1209, and/or installed from the removable medium 1211. The computer program, when executed by the processor 1201, performs the above-described functions defined in the system of the embodiments of the present disclosure. 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 an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples may include, but are 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 ROM1202 and/or the RAM 1203 and/or one or more memories other than the ROM1202 and the RAM 1203 described above.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. 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. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, 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 (16)
1. A model evaluation method, comprising:
constructing a basic database according to a plurality of stock business architecture description models, wherein the basic database comprises quality analysis information of each stock business architecture description model;
acquiring a description model of a newly added service architecture to be evaluated, wherein the description model of the newly added service architecture comprises a plurality of description entries for describing the description model of the newly added service architecture; and
and based on the quality analysis information in the basic database, performing quality evaluation on the description items of the newly added service architecture description model.
2. The method of claim 1, wherein the quality analysis information of the business architecture description model of each inventory includes at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
3. The method of claim 2, wherein the quality evaluation of the description entries of the newly added service architecture description model based on the quality analysis information in the base database comprises:
evaluating the description items of the newly added service architecture description model based on the mathematical statistic information and/or the incidence relation analysis information, and determining whether the description items of the newly added service architecture description model meet the screening condition; and
and screening out the description items which do not meet the screening condition to obtain the description items which meet the screening condition.
4. The method of claim 3, further comprising:
after the description items meeting the screening conditions are obtained, performing association rule mining on the service architecture description model of each stock and the newly added service architecture description model; and
and based on the association rule mining result, performing secondary screening on the description items meeting the screening condition through abnormality detection to screen out abnormal description items.
5. The method of claim 4, further comprising:
performing cluster analysis on the newly added service architecture description model and the service architecture description model of the stock in the basic database by using a cluster analysis method;
determining the degree of association between the newly added service architecture description model and the service architecture description model of the stock in the basic database based on the clustering analysis result; and
and determining the quality of the newly added service architecture description model based on the quality of the stock service architecture description model of which the association degree with the newly added service architecture description model meets a preset threshold value.
6. The method of claim 3, further comprising:
after the description items meeting the screening condition are obtained or abnormal description items are screened out, performing semantic analysis on the rest description items which are not analyzed in the newly added service architecture description model; and
and screening out the residual description entries which do not meet the semantic analysis condition.
7. The method of any of claims 1 to 6, further comprising:
and after the quality evaluation is carried out on the description items of the newly added service architecture description model, generating a visual chart of the quality evaluation result of the newly added service architecture description model.
8. A model evaluation system, comprising:
the system comprises a construction module, a quality analysis module and a quality analysis module, wherein the construction module is used for constructing a basic database according to a plurality of stock business architecture description models, and the basic database comprises quality analysis information of each stock business architecture description model;
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a newly added service architecture description model to be evaluated, and the newly added service architecture description model comprises a plurality of description entries for describing the newly added service architecture description model; and
and the evaluation module is used for evaluating the quality of the description items of the newly added service architecture description model based on the quality analysis information in the basic database.
9. The system of claim 8, wherein the quality analysis information of the business architecture description model for each inventory includes at least one of: the business architecture description model of each stock comprises mathematical statistical information of each constituent part of the business architecture description model of each stock, incidence relation analysis information of each constituent part, clustering information and semantic analysis information.
10. The system of claim 9, wherein the evaluation module comprises:
the evaluation unit is used for evaluating the description items of the newly added service architecture description model based on the mathematical statistic information and/or the incidence relation analysis information and determining whether the description items of the newly added service architecture description model meet the screening condition; and
and the screening unit is used for screening the description items which do not meet the screening condition to obtain the description items which meet the screening condition.
11. The system of claim 10, further comprising:
the data mining analysis module is used for mining association rules of the business architecture description model of each stock and the newly added business architecture description model after obtaining the description items meeting the screening conditions;
the screening unit is further configured to perform secondary screening on the description entries meeting the screening condition through abnormality detection based on the association rule mining result, and screen out abnormal description entries.
12. The system of claim 11, wherein the data mining analysis module is further to:
performing cluster analysis on the newly added service architecture description model and the service architecture description model of the stock in the basic database by using a cluster analysis system;
determining the degree of association between the newly added service architecture description model and the service architecture description model of the stock in the basic database based on the clustering analysis result; and
and determining the quality of the newly added service architecture description model based on the quality of the stock service architecture description model of which the association degree with the newly added service architecture description model meets a preset threshold value.
13. The system of claim 10, further comprising:
the semantic analysis module is used for performing semantic analysis on the residual description items which are not analyzed in the newly added service architecture description model after the description items meeting the screening condition are obtained or abnormal description items are screened out; and
the screening unit is also used for screening out the residual description items which do not meet the semantic analysis condition.
14. The system of any of claims 8 to 13, further comprising:
and the report module is further used for generating a visual chart of the quality evaluation result of the newly added service architecture description model after the quality evaluation is performed on the description items of the newly added service architecture description model.
15. An electronic device, comprising:
one or more processors;
a memory to store one or more instructions that,
wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
16. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of any one of claims 1 to 7.
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