CN106355439A - Knowledge base modeling method for association relation analysis - Google Patents
Knowledge base modeling method for association relation analysis Download PDFInfo
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- CN106355439A CN106355439A CN201610748111.XA CN201610748111A CN106355439A CN 106355439 A CN106355439 A CN 106355439A CN 201610748111 A CN201610748111 A CN 201610748111A CN 106355439 A CN106355439 A CN 106355439A
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- incidence relation
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a knowledge base modeling method for association relation analysis, which includes an attribute modeling stage, an object modeling phase and a relation modeling stage, wherein the attribute modeling stage uniformly configures and manages different types of information; object modeling stage defines the basic information of the object and the attribute information contained in the object; relation modeling stage carries out the business data relation modeling and management. An associated knowledge base of analysis service can be quickly constructed by using the method provided, which enables quick associated information expression of data, easy viewing and understanding, filtration of invalid data, timely response to changes in business needs, timely response to business needs, and rapid data association analysis.
Description
Technical field
The present invention relates to knowledge base modeling method, particularly a kind of knowledge base modeling method for incidence relation.
Background technology
With the development of big data storage and analysis, the data volume of user's application is increasing, and data class gets more and more,
Relation becomes increasingly complex, and data is carried out check, searches for, analyzing and become more and more difficult.Traditional business data processing method,
To existing data in system, pick out important field information and simply checked and sort out, the business not being close to the users
Demand, information indigestion；General association shows that analytical tool has done certain information processing and association to the data of system,
Still the physical relationship of data can not easily be shown, and the change with user's request and increase, Suitable content, close tying
Structure becomes extremely difficult it is difficult to adapt to new business demand, generally requires substantial amounts of development.Trace it to its cause, mainly because
It is traditional data processing and general displaying analysis is all often from data, need data is entered according to business
The certain escape of row and deformation, make data be more convenient to check, not from the needs of business itself, carry out specification to data
The management changed.
Content of the invention
Goal of the invention: it is an object of the invention to provide a kind of can solve the problem that defect present in prior art for associating
The knowledge base modeling method of relation analyses.
Technical scheme: the knowledge base modeling method for incidence relation analysis of the present invention, including model attributes rank
Section, object modeling stage and relationship modeling stage, wherein:
The model attributes stage: different types of information is carried out unify to configure and manage；
The object modeling stage: define the attribute information that the essential information of object and object comprise；
The relationship modeling stage: the data relationship of business is modeled and manages.
Further, in the described model attributes stage, attribute information is configured, described attribute information includes attribute-name
Title, attribute type, recognition rule and stacked system.
Further, user checks for convenience, and described attribute information also includes format information.
Further, user's identification for convenience, described attribute information also includes showing icon.
Further, described attribute information also includes user description information.
Further, in the described object modeling stage, the essential information of object includes object oriented, object type, object
Parent object and Object identifying rule.
Further, user's identification for convenience, the essential information of described object also includes showing icon.
Further, the essential information of described object also includes the description of object.
Further, in the described relationship modeling stage, the data relationship of business includes the class of the related object of relation, relation
Type, the level of relation, the constraint information of relation and relation weight.
Further, user's identification for convenience, the data relationship of described business also includes the display mode of relation.
Beneficial effect: compared with prior art, the present invention has a following beneficial effect:
(1) present invention, from the business of user, carries out the modeling of operation level in itself, by business datum to data
Information is standardized, and the effectiveness of data reasonably can be verified simultaneously, makes data closer to customer service, solves
Data content indigestion, data tissue is difficult in adapt to the problem of business demand change；
(2) present invention is also modeled to the relation between data, and user can easily and flexibly enter to the relation of data
Row modeling, thus conveniently realize incidence relation analysis.
Brief description
Fig. 1 is the schematic diagram of the inventive method.
Specific embodiment
The invention discloses a kind of knowledge base modeling method for incidence relation analysis, as shown in figure 1, include attribute build
Mode step section, object modeling stage and relationship modeling stage, wherein:
The model attributes stage: different types of information is carried out unify to configure and manage；
The object modeling stage: define the attribute information that the essential information of object and object comprise；
The relationship modeling stage: the data relationship of business is modeled and manages.
Below these three stages are described in detail:
The model attributes stage is standardized important step to data, and different types of name of the information, implication are united
One configuration and management, are described to the basic element of data message using the understandable language of user, strengthen user couple
The identification of information, is effectively detected to data and is filtered.Wherein it is desired to configure to attribute information, attribute information bag
Include Property Name, attribute type, format information, display icon, user description information, recognition rule and stacked system.Each belongs to
Property informative presentations are as follows:
Property Name: data name is described using customer service language；
Attribute type: the type that user understands；
Format information: format display, facilitate user to check；
Display icon: readily identified individual icon；
User description information: the understanding to this data message for the user；
Recognition rule: namely data filtering rule, for strengthening data validity monitoring；
Stacked system: data message adds up, it is to avoid lose and chaotic.
The object modeling stage is the important step to comprehension of information, analysis and displaying for the user, to data according to business element
It is modeled, facilitate user intactly to check, analyze a complete business information, rather than check, analyze multiple degrees of association
The incomplete sporadic data of not high, information.The object modeling stage is firstly the need of the essential information defining object, simultaneously need to definition
The attribute information that object comprises.The essential information of object includes object oriented, object type, display icon, the parent pair of object
Description as, Object identifying rule and object.Each essential information is described below:
Object oriented: using customer service language description object title, readily appreciate；
Object type: type is described using customer service language, readily appreciates and sort out；
Display icon: be easy to identification object information；
The parent object of object: for embodying the hierarchical relationship of object；
Object identifying rule: for strengthening data validity monitoring；
The description of object: the understanding to this object information for the user.
The relationship modeling stage is built upon the deeper understanding to data on the basis of object modeling, and the data of business is closed
System is modeled and manages.The data relationship of business include the related object of relation, the type of relation, the display mode of relation,
The level of relation, the constraint information of relation and relation weight.The data relationship of each business is described below:
The related object of relation: the object information that the relation of referring to is related to, the title including object and relating attribute；
The type of relation: indicate unidirectional, two-way or polytropic relation；
The display mode of relation: include the information such as color of relation during display, be easy to identify；
The level of relation: refer to the subdivision of relation, facilitate user to understand relation content；
The constraint information of relation: indicate the constraints of relation, mutual exclusion, contrary or unrelated；
Relation weight: show the intimate degree of relation.
The present invention quickly can build association analysiss professional knowledge storehouse according to business characteristic, can quickly complete data
Related information is expressed it is easy to checking and understanding, and can filter invalid data, can timely respond to business demand change again, and
When meet business demand, quickly realize data relation analysis.
To be introduced with a specific embodiment below: current system has a demand, to produce to understand in system
Product relation at different levels, each client, in the sales situations of different product, carry out classified finishing to the product in system and customer information.Make
Respectively product information, customer information and sales information are modeled with the inventive method, sales situations are intuitively showed
Out.
1st, the model attributes stage: the related information content of product information and customer information is modeled, describes ProductName
Title, sales volume, customer name and purchase volume.Following attribute information is configured:
(1) attribute one: name of product
Property Name: name of product
Attribute type: character string information
Format information: no
Display icon: specify an icon
User description information: the specific explanations to name of product, version
Recognition rule: product sales volume is more than 0
Stacked system: no
(2) attribute two: product sales volume
Property Name: product sales volume
Attribute type: digital information
Format information: no
Display icon: specify an icon
User description information: the explanation to product sales volume, indicate unit
Recognition rule: no
Stacked system: numeral is cumulative
(3) attribute three: customer name
Property Name: customer name
Attribute type: character string information
Format information: no
Display icon: specify an icon
User description information: the specific explanations to customer name
Recognition rule: product purchase volume is more than 0
Stacked system: no
(4) attribute four: product purchase volume
Property Name: product purchase volume
Attribute type: digital information
Format information: no
Display icon: specify an icon information
User description information: the explanation to product purchase volume, indicate unit
Recognition rule: no
Stacked system: numeral is cumulative
2nd, the object modeling stage: product information and customer information are modeled, describe every class product and each client's
Essential information.Following essential information is configured:
(1) object one: product
Object oriented: product
Object type: article
Display icon: specify an icon
The parent object of object: no
Object identifying rule: product sales volume is more than 0
The description of object: the specific explanations to product
Comprise attribute: name of product, product sales volume
(2) object two: client
Object oriented: client
Object type: unit
Display icon: specify an icon
The parent object of object: no
Object identifying rule: product purchase volume is more than 0
The description of object: the specific explanations to client unit
Comprise attribute: customer name, product purchase volume
3rd, the relationship modeling stage: the purchase relation of client and product is modeled, analyzes the purchase of each product and client
The amount of buying.Following business relations are configured:
Relation one:
The related object of relation: product and client
The type of relation: buy-sell
The display mode of relation: two-way linear
The level of relation: no rank
The constraint information of relation: purchase volume is more than 0
Relation weight: product purchase volume adds up.
Claims (10)
1. a kind of knowledge base modeling method for incidence relation analysis it is characterised in that: include model attributes stage, object and build
Mode step section and relationship modeling stage, wherein:
The model attributes stage: different types of information is carried out unify to configure and manage；
The object modeling stage: define the attribute information that the essential information of object and object comprise；
The relationship modeling stage: the data relationship of business is modeled and manages.
2. the knowledge base modeling method for incidence relation analysis according to claim 1 it is characterised in that: described attribute
In modelling phase, attribute information is configured, described attribute information includes Property Name, attribute type, recognition rule and folds
Add mode.
3. the knowledge base modeling method for incidence relation analysis according to claim 2 it is characterised in that: described attribute
Information also includes format information.
4. the knowledge base modeling method for incidence relation analysis according to claim 2 it is characterised in that: described attribute
Information also includes showing icon.
5. the knowledge base modeling method for incidence relation analysis according to claim 2 it is characterised in that: described attribute
Information also includes user description information.
6. the knowledge base modeling method for incidence relation analysis according to claim 1 it is characterised in that: described object
In modelling phase, the essential information of object includes object oriented, object type, the parent object of object and Object identifying rule.
7. the knowledge base modeling method for incidence relation analysis according to claim 6 it is characterised in that: described object
Essential information also include show icon.
8. the knowledge base modeling method for incidence relation analysis according to claim 6 it is characterised in that: described object
Essential information also include the description of object.
9. the knowledge base modeling method for incidence relation analysis according to claim 1 it is characterised in that: described relation
In modelling phase, the data relationship of business includes the related object of relation, the type of relation, the level of relation, the constraint of relation
Information and relation weight.
10. the knowledge base modeling method for incidence relation analysis according to claim 1 it is characterised in that: described industry
The data relationship of business also includes the display mode of relation.
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| CN201610748111.XA CN106355439A (en) | 2016-08-29 | 2016-08-29 | Knowledge base modeling method for association relation analysis |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107016190A (en) * | 2017-04-05 | 2017-08-04 | 北京航空航天大学 | A kind of Product maintenance and the modeling of the incidence relation of functional structure and quantization method |
| CN112462696A (en) * | 2020-08-18 | 2021-03-09 | 江苏大学 | Intelligent manufacturing workshop digital twin model construction method and system |
| CN113076086A (en) * | 2021-04-12 | 2021-07-06 | 北京元年科技股份有限公司 | Metadata management system and method for modeling model object using the same |
-
2016
- 2016-08-29 CN CN201610748111.XA patent/CN106355439A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107016190A (en) * | 2017-04-05 | 2017-08-04 | 北京航空航天大学 | A kind of Product maintenance and the modeling of the incidence relation of functional structure and quantization method |
| CN107016190B (en) * | 2017-04-05 | 2021-02-23 | 北京航空航天大学 | Product maintainability and functional structure incidence relation modeling and quantifying method |
| CN112462696A (en) * | 2020-08-18 | 2021-03-09 | 江苏大学 | Intelligent manufacturing workshop digital twin model construction method and system |
| CN113076086A (en) * | 2021-04-12 | 2021-07-06 | 北京元年科技股份有限公司 | Metadata management system and method for modeling model object using the same |
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