CN105989097A - Ontology-based knowledge base query method and system - Google Patents
Ontology-based knowledge base query method and system Download PDFInfo
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Abstract
The invention discloses an ontology-based knowledge base query method and system. The method comprises the steps of defining a hierarchical knowledge structure and establishing a plurality of knowledge bases in different domains; establishing descriptive specifications of a domain ontology and a descriptive ontology based on knowledge nodes in the knowledge bases, and generating an XML specification-based ontology description document; and performing a comparative query on a query demand and the knowledge bases based on knowledge semantic query of the ontologies, and comprehensively giving out a query result of the query demand. According to the technical scheme provided by the method and system, the query of multi-domain knowledge can be realized based on knowledge base query of the ontologies, the use convenience of the knowledge bases can be improved, and the knowledge application can be facilitated.
Description
Technical field
The present invention relates to a kind of KnowledgeBase-query method, more particularly, to a kind of knowledge based on body
Library inquiry method and system.
Background technology
With complex product development development from digitlization to intelligent direction, the management of knowledge becomes with application
For the intelligent underlying issue developed of limit product.At present in the research to complex product intelligent expert system
During, the inquiry of knowledge base is confined in same type of knowledge more, is inquired about by keyword.
General method is the specific requirement developed for complex product, it is proposed that the knowledge base structure of set form,
Select the combination between the concrete row in knowledge base or row, carry out the accurate of keyword or fuzzy query, obtain
Obtain the result meeting querying condition in knowledge base, but for user in increasing complex product development
When the demand proposing is answered, relate to the knowledge in multiple field, owing to the domain knowledge of Dispersed heterogeneous exists
Inconsistent in structure and expression-form, user typically cannot propose all of demand accurately simultaneously.
Accordingly, it is desirable to provide a kind of KnowledgeBase-query method and system based on body, for application problem
Propose query demand when, knowledge base can feedback integration inquiry after result, it is achieved complex product develop in
The inquiry of multi-field knowledge is conducive to the solution of application problem, is simultaneously also beneficial to improve what knowledge base used
Convenience, promotes the application of knowledge.
Content of the invention
It is an object of the present invention to provide a kind of KnowledgeBase-query method and system based on body, energy
Enough solutions are inconsistent due to knowledge base expression-form, and user cannot accurately propose query demand comprehensively be brought
Application problem, it is achieved the inquiry of multi-field knowledge.
For reaching above-mentioned purpose, the present invention uses following technical proposals:
A kind of KnowledgeBase-query method based on body, the method includes
The structure of knowledge of definition stratification, sets up the knowledge base of multiple different field；
Knowledge node in knowledge based storehouse is set up domain body and is described the Description standard of body, generates base
Ontology describing document in XML specification；
Based on the knowledge semantic inquiry of body, inquiry that query demand and knowledge base are compared, comprehensive
Go out the Query Result of query demand.
Preferably, described knowledge base is tree structure, supports that multilayer is decomposed, the knowledge joint obtaining after decomposition
Point can corresponding concrete knowledge content.
Preferably, in described ontology describing document
Set up the Description standard of described domain body, described field based on the logical relation between Ontological concept
The Description standard of body includes the description to realm information, conceptual information and conceptual relation information；
Set up the Description standard describing body based on body contents, described description body includes to described body
Knowledge information and the description of knowledge keyword.
Preferably, described based in the knowledge query of body, use based on dictionary Chinese words segmentation and
Based on the concept similarity computing technique of domain body, inquiry that query demand and knowledge base are compared；
Described contrast inquiry farther includes:
By query demand participle, obtain sub-concept set, each field name pair with knowledge node in domain body
Ratio, obtains potential some query demand critical fielies；
By the description body comparison of query demand critical field and each knowledge node, obtain and query demand
The knowledge record matching；
Knowledge record is analyzed, contrasts with query demand, it is thus achieved that the sequence of similarity, and with
The form display Query Result of form.
Preferably, described sub-concept is if there is multiple, then need comprehensively to obtain many sub-conceptual dependencies
Knowledge record in query demand critical field.
A kind of KnowledgeBase-query system based on body, this system includes
Structure of knowledge management module, ontologies describing module, knowledge query module；
The described structure of knowledge manages module, the structure of knowledge of definition stratification, sets up multiple different field
Knowledge base；
Described ontologies describing module, the knowledge node in knowledge based tree sets up domain body and description
The Description standard of body, generates the ontology describing document based on XML specification；
Query demand, based on the knowledge semantic inquiry of body, is compared by knowledge query module with knowledge base
To inquiry, comprehensively draw the Query Result of query demand.
Preferably, described knowledge base is that tree structure supports that multilayer is decomposed, the knowledge node obtaining after decomposition
Can corresponding concrete knowledge content.
Preferably, in described ontologies describing module
Set up the Description standard of described domain body, described field based on the logical relation between Ontological concept
The Description standard of body includes the description to realm information, conceptual information and conceptual relation information；
Set up the Description standard describing body based on body contents, described description body includes to described body
Knowledge information and the description of knowledge keyword.
Preferably, based on the knowledge query kind of body in described knowledge query module, use based on dictionary
Chinese words segmentation and the concept similarity computing technique based on domain body, by query demand and knowledge tree
Compare inquiry；；
Described contrast inquiry farther includes:
By query demand participle, obtain sub-concept set, each field name pair with knowledge node in domain body
Ratio, obtains potential some query demand critical fielies；
By the description body comparison of query demand critical field and each knowledge node, obtain and query demand
The knowledge record matching；
Knowledge record is analyzed, contrasts with query demand, it is thus achieved that the sequence of similarity, and with
The form display Query Result of form.
Preferably, described critical field is if there is multiple, then need comprehensively to obtain many sub-conceptual dependencies
Query demand critical field in knowledge record.
Beneficial effects of the present invention is as follows:
Technical scheme of the present invention compared with prior art, for application problem propose query demand when,
Knowledge base can feedback integration inquiry after result, it is achieved that based on the KnowledgeBase-query of body, Neng Goushi
In existing complex product development, the solution of the inquiry application problem of multi-field knowledge, is simultaneously also beneficial to raising and knows
Know the convenience that storehouse uses, promote the application of knowledge.
Brief description
Below in conjunction with the accompanying drawings the detailed description of the invention of the present invention is described in further detail.
Fig. 1 illustrates a kind of KnowledgeBase-query method schematic diagram based on body in the embodiment of the present invention；
Fig. 2 illustrate in the embodiment of the present invention a kind of based in the KnowledgeBase-query method and system of body for
Each knowledge node Ontology Modeling and look facility figure；
Fig. 3 illustrate in the embodiment of the present invention a kind of based in the KnowledgeBase-query method and system of body certain
The description Ontology Modeling functional schematic of knowledge node；
Fig. 4 illustrate in the embodiment of the present invention a kind of based in the KnowledgeBase-query method and system of body certain
The description body owl Fileview schematic diagram of knowledge node.
Detailed description of the invention
In order to be illustrated more clearly that the present invention, below in conjunction with preferred embodiments and drawings, the present invention is done into one
The explanation of step.Parts similar in accompanying drawing are indicated with identical reference.Those skilled in the art
It should be appreciated that following specifically described content is illustrative and be not restrictive, should not limit with this
Protection scope of the present invention.
As it is shown in figure 1, the present invention discloses a kind of KnowledgeBase-query method based on body, the method includes:
S1, the structure of knowledge of definition stratification, set up the knowledge base of multiple different field.Wherein, knowledge
It is the form of expression that tree structure is selected in storehouse, and supports that multilayer is decomposed, and the knowledge node obtaining after decomposition is corresponding
Concrete knowledge content；
S2, in knowledge base, the knowledge node in knowledge based tree is set up domain body and is stated and describe body
Description standard；The Description standard of domain body includes believing realm information, conceptual information and conceptual relation
The description of breath, for setting up based on the logical relation between Ontological concept；Domain body describes the specification of attribute
Such as table 1:
Table 1 domain body describes the specification of attribute
The Description standard describing body includes the description to knowledge information, simply keyword, is used for setting up tool
The Ontology learning of body knowledge is based on the ontology describing document of XML specification；The ontology describing specification of attribute is described such as
Table 2:
Table 2 describes the ontology describing specification of attribute
Fig. 2 shows in Knowledge Management System, and each knowledge node sets up the entrance describing body, supports
User's click right in each knowledge node of knowledge base, ejection function interface, optional " node body
The function such as change modeling " and " node ontological is checked " operates further；
Fig. 3 shows that certain knowledge node sets up the function describing body, and system provides visual modeling
Function, supports user by the self-defined key descriptors setting up certain knowledge node；
Fig. 4 shows the description body owl Fileview of certain knowledge node, by retouching that system provides
Stating after Ontology Modeling function sets up description problem, system automatically generates the owl file describing body on backstage,
Following code gives the expression example describing keyword in owl file in body of a knowledge node:
<？Xml version=" 1.0 " encoding=" ISO-8859-1 "？>
< rdf:RDF xmlns:rdf=" http://www.w3.org/1999/02/22-rdf-synatx-ns# " xmlns:
Big data=" http://www.owl-ontologies.com/# " xmlns:owl=" http://www.w3.org/2002
/ 07/owl# " xmlns:xsd=" http://www.w3.org/2001/XMLSchema# "
Xmlns:rdfs=" http://www.w3.org/2000/01/rdf-schema# " >
<owl:Class rdf:about=" the big data of http://www.owl-ontologies.com/# "/>
<rdfs:domain rdf:resource=" the big data of http://www.owl-ontologies.com/# "/>
<rdfs:subClassOf>
<owl:Class rdf:about=" http://www.owl-ontologies.com/# keyword ">
</rdfs:subClassOf>
<owl:Class rdf:about=" http://www.owl-ontologies.com/# type ">
<rdfs:subClassOf rdf:resource＝"http://www.owl-ontologies.com/#keywords"/>
</owl:Class>
<owl:Class rdf:about=" http://www.owl-ontologies.com/# the first authors ">
<rdfs:subClassOf rdf:resource＝"http://www.owl-ontologies.com/#keywords"/>
</owl:Class>
<owl:Class rdf:about=" http://www.owl-ontologies.com/# Chinese exercise question ">
<rdfs:subClassOf rdf:resource＝"http://www.owl-ontologies.com/#keywords"/>
</owl:Class>
<owl:Class rdf:about=" http://www.owl-ontologies.com/# Chinese key ">
<rdfs:subClassOf rdf:resource＝"http://www.owl-ontologies.com/#keywords"/>
</owl:Class>
<owl:Class rdf:about=" other authors of http://www.owl-ontologies.com/# ">
<rdfs:subClassOf rdf:resource＝"http://www.owl-ontologies.com/#keywords"/>
</owl:Class>
</rdf:RDF>
The keyword of definition include " type ", " the first authors ", " Chinese exercise question ", " Chinese key ",
" other authors " etc..
S3, the knowledge semantic inquiry based on body, by using based on the Chinese words segmentation of dictionary and base
In the concept similarity computing technique of domain body, query demand and knowledge base are carried out three comparisons inquiry,
Comprehensively provide the Query Result of query demand.If query demand can provide more specific description information,
Then can filter out the record of redundancy further, obtain retrieving more accurately result；
Wherein contrast inquiry to farther include:
S31, by query demand participle, obtain sub-concept set, each field with knowledge node in domain body
Name contrast, comprehensively provides the Query Result of query demand.If there is multiple critical fielies, then total score
Analyse the knowledge record in multiple field；
S32, the description body comparison by query demand and each knowledge node, obtain and query demand phase
The knowledge record joined；
S33, knowledge record in described critical field is analyzed after, contrast with query demand, obtain
Obtain the sequence of similarity, and show Query Result in table form.
The invention also discloses a kind of KnowledgeBase-query system based on body, this system includes the structure of knowledge
Management module, ontologies describing module, knowledge query module.
The structure of knowledge manage module, support use tree and management design teacher accumulation and application set
Meter knowledge, forms knowledge base；Ontologies describing module, supports that the knowledge node in knowledge based tree is entered
Row ontology describing, supports to realize the knowledge query based on body；Knowledge query module, provides based on body
Knowledge query algorithm, support to realize the inquiry of knowledge according to ontologies.
The structure of knowledge manages module, the structure of knowledge of definition stratification, sets up the knowledge of multiple different field
Storehouse.Wherein, knowledge base selects tree structure is the form of expression, and supports that multilayer is decomposed, and obtains after decomposition
The corresponding concrete knowledge content of knowledge node；
Ontologies describing module, in knowledge base, the knowledge node in knowledge based tree sets up field originally
The Description standard of body is stated and described to body；The Description standard of domain body includes believing realm information, concept
Breath and the description of conceptual relation information, for setting up based on the logical relation between Ontological concept；This is described
The Description standard of body includes the description to knowledge information, simply keyword, for setting up the basis of concrete knowledge
Body generates the ontology describing document based on XML specification.
Knowledge query module, based on the knowledge semantic inquiry of body, is divided by using the Chinese based on dictionary
Query demand and knowledge base are carried out three by word technology and the concept similarity computing technique based on domain body
Secondary comparison is inquired about, and comprehensively provides the Query Result of query demand.Wherein contrast step to include: first will look into
Inquiry demand participle, obtains sub-concept set.Based on the domain body having built, by query demand and field
Knowledge node each field name comparison in body, obtains potential some query demand critical fielies.If deposited
Many sub-concepts, then need knowing in the comprehensive query demand critical field obtaining many sub-conceptual dependencies
Memorize is recorded.Based on the description body having built, by retouching of query demand critical field and each knowledge node
State body comparison, obtain based on semantic ranking results, and then can obtain matching with query demand
Knowledge record；All of knowledge record is analyzed, and query demand carries out third time comparison, it is thus achieved that
The sequence of similarity, and show Query Result in table form at Query Result interface.If inquiry needs
The more specific description information that can provide is provided, then can filter out the record of redundancy further, obtain more
Accurate retrieval result.
In sum, technical scheme of the present invention, when proposing query demand for application problem, knows
Know storehouse can feedback integration inquiry after result, it is achieved that based on the KnowledgeBase-query of body, be capable of
In complex product development, the solution of the inquiry application problem of multi-field knowledge, is simultaneously also beneficial to improve knowledge
The convenience that storehouse uses, promotes the application of knowledge.
Obviously, the above embodiment of the present invention is only for clearly demonstrating example of the present invention, and
It is not the restriction to embodiments of the present invention, for those of ordinary skill in the field,
Can also make other changes in different forms on the basis of described above, here cannot be to all
Embodiment give exhaustive, every belong to the obvious change that technical scheme extended out
Change or change the row still in protection scope of the present invention.
Claims (10)
1. the KnowledgeBase-query method based on body, it is characterised in that described the method includes
The structure of knowledge of definition stratification, sets up the knowledge base of multiple different field；
Knowledge node in knowledge based storehouse is set up domain body and is described the Description standard of body, generates base
Ontology describing document in XML specification；
Based on the knowledge semantic inquiry of body, inquiry that query demand and knowledge base are compared, comprehensive
Go out the Query Result of query demand.
2. querying method according to claim 1, it is characterised in that described knowledge base is tree-like knot
Structure, supports that multilayer is decomposed, and the knowledge node obtaining after decomposition can corresponding concrete knowledge content.
3. querying method according to claim 1, it is characterised in that in described ontology describing document
Set up the Description standard of described domain body, described field based on the logical relation between Ontological concept
The Description standard of body includes the description to realm information, conceptual information and conceptual relation information；
Set up the Description standard describing body based on body contents, described description body includes to described body
Knowledge information and the description of knowledge keyword.
4. querying method according to claim 1, it is characterised in that the described knowledge based on body
In inquiry, the Chinese words segmentation based on dictionary and the concept similarity based on domain body is used to calculate skill
Art, inquiry that query demand and knowledge base are compared；
Described contrast inquiry farther includes:
By query demand participle, obtain sub-concept set, each field name pair with knowledge node in domain body
Ratio, obtains potential some query demand critical fielies；
By the description body comparison of query demand critical field and each knowledge node, obtain and query demand
The knowledge record matching；
Knowledge record is analyzed, contrasts with query demand, it is thus achieved that the sequence of similarity, and with
The form display Query Result of form.
5. querying method according to claim 4, it is characterised in that described sub-concept if there is
Multiple, then need the knowledge record in the comprehensive query demand critical field obtaining many sub-conceptual dependencies.
6. the KnowledgeBase-query system based on body, it is characterised in that this system described includes
Structure of knowledge management module, ontologies describing module, knowledge query module；
The described structure of knowledge manages module, the structure of knowledge of definition stratification, sets up multiple different field
Knowledge base；
Described ontologies describing module, the knowledge node in knowledge based tree sets up domain body and description
The Description standard of body, generates the ontology describing document based on XML specification；
Query demand, based on the knowledge semantic inquiry of body, is compared by knowledge query module with knowledge base
To inquiry, comprehensively draw the Query Result of query demand.
7. querying method according to claim 6, it is characterised in that described knowledge base is tree-like knot
Structure supports that multilayer is decomposed, and the knowledge node obtaining after decomposition can corresponding concrete knowledge content.
8. querying method according to claim 6, it is characterised in that described ontologies describes mould
In block
Set up the Description standard of described domain body, described field based on the logical relation between Ontological concept
The Description standard of body includes the description to realm information, conceptual information and conceptual relation information；
Set up the Description standard describing body based on body contents, described description body includes to described body
Knowledge information and the description of knowledge keyword.
9. querying method according to claim 6, it is characterised in that in described knowledge query module
Based on the knowledge query kind of body, use based on the Chinese words segmentation of dictionary and general based on domain body
Read Similarity Measure technology, inquiry that query demand and knowledge tree are compared；；
Described contrast inquiry farther includes:
By query demand participle, obtain sub-concept set, each field name pair with knowledge node in domain body
Ratio, obtains potential some query demand critical fielies；
By the description body comparison of query demand critical field and each knowledge node, obtain and query demand
The knowledge record matching；
Knowledge record is analyzed, contrasts with query demand, it is thus achieved that the sequence of similarity, and with
The form display Query Result of form.
10. querying method according to claim 9, it is characterised in that if described critical field
Exist multiple, then need the knowledge note in the comprehensive query demand critical field obtaining many sub-conceptual dependencies
Record.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107329955A (en) * | 2017-06-30 | 2017-11-07 | 武汉工程大学 | A kind of computational methods of ontology key element instance properties similarity |
| CN107480140A (en) * | 2017-08-23 | 2017-12-15 | 北京仿真中心 | A kind of intelligent case library implementation method based on crowd's wound |
| CN108268505A (en) * | 2016-12-30 | 2018-07-10 | 西门子公司 | Modeling method and device based on semantic knowledge |
| CN108536872A (en) * | 2018-04-27 | 2018-09-14 | 武汉文都信息技术有限公司 | Optimize the method and apparatus of knowledge base structure |
| CN110083749A (en) * | 2019-04-11 | 2019-08-02 | 艾伯资讯（深圳）有限公司 | The retrieval quickly developed for software, multiplexing, environmental structure system and method |
| CN110516079A (en) * | 2019-08-29 | 2019-11-29 | 北京大学 | A kind of RDF object model class hierarchy tree method for building up and system |
| CN112734213A (en) * | 2020-12-30 | 2021-04-30 | 大连海事大学 | Body-based highway bridge technical condition inspection and evaluation method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101059806A (en) * | 2007-06-06 | 2007-10-24 | 华东师范大学 | Word sense based local file searching method |
| CN101388026A (en) * | 2008-10-09 | 2009-03-18 | 浙江大学 | Semantic indexing method based on field ontology |
| CN101655862A (en) * | 2009-08-11 | 2010-02-24 | 华天清 | Method and device for searching information object |
| CN102184194A (en) * | 2011-04-20 | 2011-09-14 | 上海交通大学 | Ontology-based knowledge map drawing system |
| CN102646095A (en) * | 2011-02-18 | 2012-08-22 | 株式会社理光 | Object classifying method and system based on webpage classification information |
| CN103020074A (en) * | 2011-09-23 | 2013-04-03 | 倪毅 | Object-level search technique based on main body |
| CN104123609A (en) * | 2014-07-05 | 2014-10-29 | 华中科技大学 | Metro construction risk knowledge construction method based on noumenon |
-
2015
- 2015-02-12 CN CN201510076659.XA patent/CN105989097A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101059806A (en) * | 2007-06-06 | 2007-10-24 | 华东师范大学 | Word sense based local file searching method |
| CN101388026A (en) * | 2008-10-09 | 2009-03-18 | 浙江大学 | Semantic indexing method based on field ontology |
| CN101655862A (en) * | 2009-08-11 | 2010-02-24 | 华天清 | Method and device for searching information object |
| CN102646095A (en) * | 2011-02-18 | 2012-08-22 | 株式会社理光 | Object classifying method and system based on webpage classification information |
| CN102184194A (en) * | 2011-04-20 | 2011-09-14 | 上海交通大学 | Ontology-based knowledge map drawing system |
| CN103020074A (en) * | 2011-09-23 | 2013-04-03 | 倪毅 | Object-level search technique based on main body |
| CN104123609A (en) * | 2014-07-05 | 2014-10-29 | 华中科技大学 | Metro construction risk knowledge construction method based on noumenon |
Non-Patent Citations (1)
| Title |
|---|
| 饶元等: "基于本体的XML知识表示方法研究", 《微电子学与计算机》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108268505A (en) * | 2016-12-30 | 2018-07-10 | 西门子公司 | Modeling method and device based on semantic knowledge |
| CN107329955A (en) * | 2017-06-30 | 2017-11-07 | 武汉工程大学 | A kind of computational methods of ontology key element instance properties similarity |
| CN107329955B (en) * | 2017-06-30 | 2020-09-15 | 武汉工程大学 | Method for calculating attribute similarity of geographic ontology element instances |
| CN107480140A (en) * | 2017-08-23 | 2017-12-15 | 北京仿真中心 | A kind of intelligent case library implementation method based on crowd's wound |
| CN108536872A (en) * | 2018-04-27 | 2018-09-14 | 武汉文都信息技术有限公司 | Optimize the method and apparatus of knowledge base structure |
| CN108536872B (en) * | 2018-04-27 | 2020-12-25 | 湖北时代万新国际教育发展有限公司 | Method and device for optimizing knowledge base structure |
| CN110083749A (en) * | 2019-04-11 | 2019-08-02 | 艾伯资讯（深圳）有限公司 | The retrieval quickly developed for software, multiplexing, environmental structure system and method |
| CN110516079A (en) * | 2019-08-29 | 2019-11-29 | 北京大学 | A kind of RDF object model class hierarchy tree method for building up and system |
| CN110516079B (en) * | 2019-08-29 | 2022-04-29 | 北京大学 | RDF object model class hierarchical tree establishing method and system |
| CN112734213A (en) * | 2020-12-30 | 2021-04-30 | 大连海事大学 | Body-based highway bridge technical condition inspection and evaluation method |
| CN112734213B (en) * | 2020-12-30 | 2023-12-15 | 大连海事大学 | Body-based highway bridge technical condition inspection and evaluation method |
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