WO2005052720A2

WO2005052720A2 - Knowledge modeling system using ontology

Info

Publication number: WO2005052720A2
Application number: PCT/KR2003/002896
Authority: WO
Inventors: Shin-Young Lim; Young-Gook Ha; Jae-Hong Kim; Cheon-Shu Park; Joo-Chan Sohn; Ho-Sang Ham
Original assignee: Electronics And Telecommunications Research Institute
Priority date: 2003-11-28
Filing date: 2003-12-30
Publication date: 2005-06-09
Also published as: KR20050051864A; AU2003288776A1; WO2005052720A3; AU2003288776A8; KR100505970B1

Abstract

An ontology-based knowledge modeling system comprising: a conceptual modeling (100) unit for classifying a knowledge region of a specific domain, performing detailed modeling on a conceptual detailed domain within the classified knowledge region, and configuring a specific domain knowledge model (110) having the respective detailed models (120) as a set; a logical modeling (200) unit for configuring a schema-based logical model (210) based on respective detailed schemas (220) defined by referring to detailed models that correspond to the detailed schemas one by one from the set of the specific domain knowledge model of the conceptual modeling unit; and a physical modeling (300) unit for configuring a physical knowledge reposit model (310) by a detailed data repository (320) for physically analyzing the schemas defined by respective detailed schemas in the logical modeling process, and a mediator (340) for controlling an external interface (330) of the detailed data repository.

Description

KNOWLEDGE MODELING SYSTEM AND METHOD USING ONTOLOGY

CROSS REFERENCE TO RELATED APPLICATION This application claims priority to and the benefit of Korea Patent

Application No. 2003-85529 filed on November 28, 2003 in the Korean

Intellectual Property Office, the content of which is incorporated herein by

reference.

BACKGROUND OF THE INVENTION

(a) Field of the Invention

The present invention relates to an ontology-based knowledge modeling system and method for providing various knowledge services using

a knowledge base and semantic network on knowledge of a specific domain. (b) Description of the Related Art

Conventional knowledge techniques are provided in the expert

system format, and a broker model based on distributed middleware and a

P2P (peer-to-peer) interaction model are generally applied to the knowledge-

based expert system. When the above-noted knowledge models are established in a

predetermined modeling process, it is required to discard schemas and

contents of the knowledge base built on the pre-established model basis and

build new ones when subsequently attempting to modify or extend the

knowledge. That is, it is impossible for the conventional knowledge modeling process to synchronize the knowledge base with the modification of the knowledge model. It is also impossible to maintain the inter-compatibility of classification systems in the integration and extension process between knowledge bases of close or similar expert domains since knowledge classification methods and processes are performed for each knowledge base. Also, the conventional knowledge modeling process does not allow repository and search functions during the process of integrating, extending, and linking with the expert knowledge bases of close or similar domains since the conventional process does not use the object-orientation method that guarantees standardization and inter-compatibility during the knowledge reposit and search process. In particular, the knowledge inference process on the knowledge base allows no inter-compatibility or extendibility because the process is individually built according to an applied inference algorithm, an inference service coverage range, and a realized inference engine. The knowledge between a built knowledge base and a similar knowledge base cannot be shared since internal structures of the knowledge bases and knowledge modeling methods are different from each other. The conventional knowledge services based on the conventional knowledge base have no internationally standardized knowledge modeling methods, knowledge base rules, and knowledge inference methods, and hence, it is impossible to share or integrate the individually built inference methods in the future process where the individually built knowledge bases and corresponding knowledge services are extended or integrated, so it is needed to build a new inference method. The above-built knowledge modeling system provides incomplete methods for controlling knowledge access ranges and knowledge service ranges, and causes security and privacy violation problems because of structural differences between the knowledge bases and the knowledge modeling systems when attempting inter-sharing, linking, extension, and integration between the knowledge bases, and because of absence of unified methods for controlling supply ranges of knowledge, and knowledge access range for each knowledge service user grade. As a result, the conventional knowledge techniques have problems in interoperability of knowledge services using the knowledge base and the semantic network, knowledge sharing, scalability, security, and privacy, and provide no fundamental solutions.

SUMMARY OF THE INVENTION

It is an advantage of the present invention to provide an ontology- based knowledge modeling method and system for effectively providing expert knowledge required by a corresponding task of a corresponding domain through modeling, classification, repository, search, inference, integration, and extension by applying the ontology method to the expert knowledge of a specific domain for the purpose of the knowledge services. To achieve the advantage, knowledge models including a conceptual model, a logical model, a physical model, and an ontology-based object-oriented model are produced to provide appropriate knowledge services according to a knowledge service request by a user. In one aspect of the present invention, an ontology-based knowledge modeling method comprises: (a) classifying knowledge of a specific domain as a conceptual model, a logical model, and a physical model to thus perform knowledge modeling, and defining the knowledge modeling; (b) defining a data reposit component and an interface component from among the components of the physical model defined in (a) as object oriented models which configure an ontology set for external link and extension, and allowing the data reposit component and the interface component to be linked with each other; (c) building a knowledge service system including an ontology-based knowledge base and a semantic network so as to perform one of tasks which include access, inference, mapping, translation, visualization, authoring, and merging of the ontology of the object oriented model established in (b); and (d) performing ontology system analysis so as to validate whether one of functions that include interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system built in (c) is provided. The (a) comprises: distinguishing a knowledge region of the specific domain, and performing detailed modeling of a conceptual detailed domain within the knowledge domain to configure a specific domain knowledge model that has the respective detailed models as a set, thereby executing a conceptual modeling process; configuring a schema-based logical model

based on respective detailed schemas defined by referring to detailed

models which correspond to the detailed schemas one by one from the set of

the specific domain knowledge model in the conceptual modeling process,

thereby executing a logical modeling process; and configuring a physical

knowledge reposit model by a detailed data repository for physically

analyzing the schemas defined by respective detailed schemas in the logical

modeling process, and a mediator for controlling an external interface of the

detailed data repository, thereby executing a physical modeling process. The specific domain knowledge model and the schema-based logical

model are linked with each other, and the schema-based logical model and the physical knowledge reposit model are linked with each other.

The knowledge service system in (c) has hierarchies of a knowledge

base build layer, an ontology-based knowledge base support layer, an

ontology platform describe layer, and a knowledge base link and

management layer.

The knowledge base comprises a T-Box (terminology box) for

defining the terminologies, and an A-Box (assertion box) for defining

relationship establishment between the terminologies. The ontology system analysis in (d) comprises at least one of

analysis functions including ontology analysis, ontology structure analysis

caused by ontology mapping and merging, ontology inference analysis, and

ontology object model analysis.

In another aspect of the present invention, an ontology-based knowledge modeling system comprises: a conceptual modeling unit for classifying a knowledge region of a specific domain, performing detailed modeling on a conceptual detailed domain within the classified knowledge region, and configuring a specific domain knowledge model having the respective detailed models as a set; a logical modeling unit for configuring a schema-based logical model based on respective detailed schemas defined by referring to detailed models that correspond to the detailed schemas one by one from the set of the specific domain knowledge model of the conceptual modeling unit; and a physical modeling unit for configuring a physical knowledge reposit model by a detailed data repository for physically analyzing the schemas defined by respective detailed schemas in the logical modeling process, and a mediator for controlling an external interface of the detailed data repository. The respective models in the conceptual modeling unit and the logical modeling unit, and the respective models in the logical modeling unit and the physical modeling unit, are linked with each other, and are used as reference models, and lower models and higher models of the respective units are linked with each other and mapped in the horizontal direction. The knowledge base build layer comprises: a knowledge base for defining definitions of terminologies and relation establishment between the respective terminologies; and a web-based ontology for representing the knowledge base by using a network web-based format. BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate an embodiment of the invention, and, together with the description, serve to explain the principles of the invention: FIG. 1 shows a configuration of a knowledge base according to a preferred embodiment of the present invention; FIG. 2 shows a configuration of an ontology-based knowledge base according to a preferred embodiment of the present invention; and FIG. 3 shows an exemplified configuration of an ontology-based knowledge service system by a physical modeling unit of FIG. 2.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following detailed description, only the preferred embodiment of the invention has been shown and described, simply by way of illustration of the best mode contemplated by the inventor(s) of carrying out the invention. As will be realized, the invention is capable of modification in various obvious respects, all without departing from the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not restrictive. FIG. 1 shows a configuration of a knowledge base 10 according to a preferred embodiment of the present invention. The knowledge base 10 comprises a T-Box 11 and an A-Box 12. The T-Box 1 1 defines terminologies, and the A-Box 12 defines

assertions which are definitions of relation establishment between concepts

of respective terminologies. As to knowledge inference, a part relating to the

terminologies from the contents of a configured knowledge base is used to

find a knowledge service of the related expert domain.

Knowledge modeling is a process for embodying a knowledge

configuration on the knowledge of a specific domain. The knowledge

modeling process has a knowledge classification of a specific domain, and a

constraint of knowledge representation within the knowledge classification

range, performs knowledge modeling on a conceptual detailed domain, and

collects the respective detailed knowledge models as a single set to thus configure a conceptual model. The conceptual model is used as a reference

model to configure a logical model, the conceptual model is modeled as a

logical model format based on a schema of the logical model, and respective

detailed schemas perform a schema definition with reference to detailed

models for each of the set of the conceptual models.

FIG. 2 shows a configuration of an ontology-based knowledge

modeling system according to a preferred embodiment of the present

invention. As shown, the ontology-based knowledge modeling system

comprises a conceptual modeling unit 100, a logical modeling unit 200, and

a physical modeling unit 300.

The conceptual modeling unit 100 defines a specific domain

knowledge model 1 10, defines detailed knowledge models 120 for describing the specific domain based on the defined model, and defines them as a set of the knowledge model of the specific domain. The logical modeling unit 200 defines a schema-based logical model

210 on the conceptual modeling unit 100 and the conceptual model, defines detailed schemas 220 on the set of the detailed conceptual models which are lower than the conceptual models in their hierarchy, and defines the detailed schemas 220 as a schema set. The physical modeling unit 300 defines detailed physical components as a single physical detailed ontology set, and defines a mediator 340 for supporting interlinks between the detailed physical components. In this instance, each detailed physical component has a detailed data repository 320 for physically analyzing the schemas defined by the respective detailed schemas, and a corresponding interface 330 as a single unit. The specific domain knowledge model 110 of the conceptual modeling unit 100 and the schema-based logical model 210 of the logical modeling unit 200 are linked with each other, and the schema-based logical model 210 and a physical knowledge repository model 310 of the physical modeling unit 300 are linked with each other. Functions of the link at the respective modeling units 100 to 300 allow easy reference to the models built for each stage, and allow a structure for accurately reflecting the modification of the knowledge models including the physical knowledge repository model 310 when a knowledge region of a specific domain is varied. Also, the detailed knowledge model 120, the detailed schema 220, and the detailed data repository 320 in each stage are linked to their upper models, and they are mapped to each other. The mapping relation shows that they correspond to the configuration contents of the detailed set at a 1 :1 ratio. The interface 330 and the mediator 340 of the physical modeling unit 300 control the external interface of the lower detailed data repository 320. The mediator 340 is the actual body of the ontology object-oriented model on the knowledge model basis, and its major functions are to initially generate, maintain, and manage a physical schema mapping table of the knowledge base, an ontology index mapping table, an OIAI (ontology inference algorithm identifier) table, a knowledge base service profile management table, a knowledge base service profile mapping table, and a user profile management table per knowledge base user grade, and accordingly guarantees interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system including the ontology- based knowledge base and the semantic network. FIG. 3 shows an exemplified configuration of an ontology-based knowledge service system by a physical modeling unit of FIG. 2. The ontology-based knowledge service system has four layers and is built from the object-oriented model of the ontology-based knowledge modeling system. As shown, the ontology-based knowledge service system comprises a knowledge base build layer 500, an ontology-based knowledge base support layer 600, an ontology platform describe layer 700, and a knowledge base link and management layer 800. The knowledge base build layer 500 has the knowledge. Data of a database 510 in the knowledge base build layer 500 provides primitive knowledge which is a basic unit for a knowledge base when building the knowledge base 520 of a specific domain. A web-based ontology 530 displays the knowledge base in the Internet-based format. The knowledge base 520 comprises a T-Box and an A-Box as shown in FIG. 1. The ontology-based knowledge base support layer 600 comprises an ontology access unit 640, an ontology analyzer 610, and an ontology inference unit 630 on the basis of an ontology-based object model 620. The ontology analyzer 610 is used for an ontology system analysis process for checking the scalability and operability of the system. The ontology analyzer 610 includes operations of an ontology analysis, an ontology configuration analysis following mapping and combination of the ontology, an ontology inference analysis, and an ontology object model analysis so that the system may verify further scalability and interoperability. The operation of an ontology analysis includes a simple syntactic analysis, a semantic consistency analysis, and a search of name conflict and syntactic conflict. The operation of an ontology configuration analysis following mapping and combination of the ontology includes syntax mapping and merging result analysis on a class and a property value of an ontology node, and a configuration analysis on the total ontology. The operation of an ontology inference analysis includes ontology

relation analysis for validating class relation consistency on the node and the

consistency on the integrated class structure, fact consistency analysis on

the knowledge, and analysis on an implication relation, syntactic structure, classification, and incompleteness.

The operation of an ontology object model analysis analyses

operations of initially generating, maintaining, and managing a physical

schema mapping table of the knowledge base, an ontology index mapping

table, an OIAI table, a knowledge base service profile management table, a

knowledge base service profile mapping table, and a user profile

management table per knowledge base user grade to thus verify supply

states of interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system.

The ontology access unit 640 accesses a knowledge repository, built in the knowledge base, for storing data in the ontology format, according to a

query request by a user, and provides functions of storing, referring to,

modifying, and deleting the knowledge. The ontology access unit 640 further

provides functions of adding, deleting, and modifying the ontology object

model. The ontology inference unit 630 provides an operation of interfacing

a definition language for representing the relation caused by the definition of

an object which configures the ontology object model, a knowledge base

query model language for an agent that provides the knowledge base service,

and a corresponding message, an operation of processing inquiries on the ontology-based knowledge base, and an operation of inferring the ontology. The ontology platform describe layer 700 comprises an ontology mapper 710, an ontology translator 720, an ontology component visualization describer 730, and an ontology engine drive describer 740. The ontology mapper 710 performs a temporary mapping function so as to improve knowledge service levels between partially built knowledge bases when the ontology-based knowledge bases 520 have an implication relation, a vertical relation, a horizontal relation, and an adjacency relation according to the knowledge configuring contents. The ontology mapper 710 includes a per-node similarity search result table, an inter-node mapping rule table, a mapping link identifier, and a profile table. When a user submits a knowledge service query, a knowledge base service agent uses an external knowledge base access provided by the ontology access unit 640 and uses the ontology mapper 710 for the knowledge which is not provided in an internal knowledge base, accesses the knowledge provided in an expert knowledge region, and provides a knowledge query result desired by the user to the user. The ontology translator 720 translates different knowledge representation languages and query model languages when an ontology is queried, in order to solve linguistic constraint problems of the definition language for representing the relation caused by the definition of the object which configures the ontology object model 620 as a role, and the knowledge base query model language for an agent that performs the knowledge base service.

The ontology component visualization describer 730 visually describes the ontology components, and the ontology engine drive describer

740 describes the ontology engine drives. The knowledge base link and management layer 800 comprises an ontology merger 810, an ontology authoring describer 820, and a knowledge base ontology management describer 830. The ontology merger 810 validates two ontology indices of the ontology-based knowledge bases to perform syntax analysis, semantics analysis, concept-terminology analysis, concept-definition analysis, and taxonomic analysis for each ontology node respectively when new knowledge is added to the existing knowledge base and when links with high similarities are found from among the existing knowledge bases to merge the existing knowledge bases. The ontology merger 810 checks omitted terminologies, an omitted part of knowledge contents, omitted knowledge, correspondence states of pattern constraint items, omission states of terminology definitions from the conflicted parts of between the two ontology nodes according to the analysis results, and manually corrects the checked contents to thus solve the conflict problem of the two pieces of the ontology, and merges the two pieces of the ontology in the order of from the nodes having the highest similarity in the ontology index. The above-described ontology-based knowledge modeling method defines a conceptual model, a logical model, and a physical model which is the ultimate one of the knowledge model. The detailed data repository 320 and the interface 330 which are physical components of the physical model are defined as a single object to build a four-layered object-oriented model in order to perform operations for linking with the external part of the object and for extension. The method defines methods for accessing, inferring, mapping, translating, visualizing, authoring, and merging the ontology in order to build a knowledge service system based on detailed roles of respective objects defined in the object-oriented model and object type ontology, and to solve the problems of interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system. The method performs an ontology system analysis for checking the solving states of the problems of interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system, and the system performance. As described, the ontology-driven knowledge modeling method and system uses the ontology and the object-oriented model technique to solve the problems of interoperability, knowledge sharing, scalability, security, and privacy between different knowledge bases and knowledge services, and also allows a user to receive a desired knowledge service through a query for requesting a knowledge service of a specific domain. The knowledge modeling is classified as conceptual, logical, and physical modeling to produce the ontology-based object-oriented model, and it allows correlation through horizontal mapping between the components within the model, and accordingly, the interoperability is possible when the knowledge bases, inference algorithms applied during the knowledge inference process, inference service supplying ranges, and internal structures of the realized inference engines are different. The problem of different structures of the knowledge base schemas and contents is solved by using an object-oriented modeling method that allows synchronization of schemas and structures, and accordingly, consistent functions and services of integration, extension, linking of adjacent knowledge of a specific domain, and of access and security of the knowledge base can be provided. While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

WHAT IS CLAIMED IS:

1. An ontology-based knowledge modeling method comprising: (a) classifying knowledge of a specific domain as a conceptual model, a logical model, and a physical model to thus perform knowledge modeling, and defining the knowledge modeling; (b) defining a data reposit component and an interface component from among the components of the physical model defined in (a) as object oriented models which configure an ontology set for external link and extension, and allowing the data reposit component and the interface component to be linked with each other; (c) building a knowledge service system including an ontology-based knowledge base and a semantic network so as to perform one of tasks which include access, inference, mapping, translation, visualization, authoring, and merging of the ontology of the object oriented model established in (b); and (d) performing ontology system analysis so as to validate whether one of functions that include interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system built in (c) is provided.

2. The method of claim 1 , wherein (a) comprises: distinguishing a knowledge region of the specific domain, and performing detailed modeling of a conceptual detailed domain within the knowledge domain to configure a specific domain knowledge model that has the respective detailed models as a set, thereby executing a conceptual modeling process; configuring a schema-based logical model based on respective detailed schemas defined by referring to detailed models which correspond to the detailed schemas one by one from the set of the specific domain knowledge model in the conceptual modeling process, thereby executing a logical modeling process; and configuring a physical knowledge reposit model by a detailed data repository for physically analyzing the schemas defined by respective detailed schemas in the logical modeling process, and a mediator for controlling an external interface of the detailed data repository, thereby executing a physical modeling process.

3. The method of claim 2, wherein the specific domain knowledge model and the schema-based logical model are linked with each other, and the schema-based logical model and the physical knowledge reposit model are linked with each other.

4. The method of claim 2, wherein the detailed model is linked with the specific domain knowledge model, the detailed schema is linked with the schemarbased logical model, the detailed data repository is linked with the physical knowledge reposit model, and they are mapped to each other in the horizontal direction.

5. The method of claim 2, wherein the mediator of the physical modeling process performs at least one of functions that include an initial generation function, maintenance function, and management function on one of a physical schema mapping table, an ontology index mapping table, an ontology inference algorithm identifier table, a knowledge base service profile management table, and a user profile management table per knowledge base user grade, the tables being of the knowledge base.

6. The method of claim 5, wherein the mediator guarantees at least one of the functions that include interoperability, knowledge sharing, scalability, security, and privacy of the knowledge service system.

7. The method of claim 1 , wherein the knowledge service system in

(c) has hierarchies of a knowledge base build layer, an ontology-based knowledge base support layer, an ontology platform describe layer, and a knowledge base link and management layer.

8. The method of claim 7, wherein the knowledge base build layer comprises a database for providing primitive knowledge, a knowledge base for defining terminologies and relationship establishment for knowledge inference, and a web-based ontology for representing the knowledge base by using a web format.

9. The method of claim 8, wherein the knowledge base comprises a T-Box (terminology box) for defining the terminologies, and an A-Box

(assertion box) for defining relationship establishment between the terminologies.

10. The method of claim 9, wherein the ontology-based knowledge base support layer includes at least one of ontology access, analysis, and inference based on the ontology-based object model.

11. The method of claim 10, wherein the ontology access provides functions for accessing a knowledge repository stored in the knowledge base in the ontology format according to a query request by a user, and performing at least one operation of repositing, reference, modification, and deletion of the knowledge, provides functions of addition, deletion, and modification on the ontology object model, and provides functions of providing each knowledge set in an external knowledge base and an internal knowledge base to the internal side and the external side respectively.

12. The method of claim 10, wherein the ontology inference provides a definition language for representing relations, caused by definition of the object which configures the ontology object model, as roles, a knowledge base query model language for an agent that performs the knowledge base service, a corresponding message interface, query processing on the ontology-based knowledge base, and an ontology inference function.

13. The method of claim 10, wherein the ontology platform describe layer includes at least one of ontology mapping, ontology component visualization, and ontology engine driving.

14. The method of claim 13, wherein the ontology mapping includes at least one of a per-node similarity search result table, an inter-node mapping rule table, a mapping link identifier, and a profile table.

15. The method of claim 11 or 14, wherein the ontology access and the ontology mapping allow access to the internal knowledge base and the external knowledge base according to a knowledge service query request by a user, and access to the knowledge provided in the expert knowledge region by using the ontology mapping to provide knowledge query results desired by the user.

16. The method of claim 13, wherein the ontology translation translates different knowledge representation languages and query model languages when the ontology is queried.

17. The method of claim 7, wherein the knowledge base link and management layer includes at least one of ontology merging, ontology authoring, and ontology managing for the knowledge base.

18. The method of claim 17, wherein the ontology merging provides functions of adding new knowledge to the knowledge base, or merging the knowledge bases when a plurality of links with high similarities between the knowledge bases are found.

19. The method of claim 17, wherein the ontology merging validates two ontology indices of the ontology-based knowledge bases to perform at least one of tasks that include syntax analysis, semantics analysis, concept- terminology analysis, concept-definition analysis, and taxonomic analysis for each ontology node, and checks and corrects terminology omission for conflict avoidance, an omitted part of the knowledge contents, omitted knowledge, corresponding states of pattern constraint items, and omission of terminology definition in the parts where a conflict is generated between the ontology nodes from among the analysis results.

20. The method of claim 1, wherein the ontology system analysis in (d) comprises at least one of analysis functions including ontology analysis, ontology structure analysis caused by ontology mapping and merging, ontology inference analysis, and ontology object model analysis.

21. The method of claim 20, wherein the ontology analysis includes at least one of analysis functions including syntactic simple analysis, semantic consistency analysis, name conflict and syntactic conflict search.

22. The method of claim 20, wherein the ontology structure analysis caused by ontology mapping and merging includes at least one of analysis functions including syntactic mapping and merging result analysis on the class and the property values of the ontology node, and structure analysis on the total ontology.

23. The method of claim 20, wherein the ontology inference analysis includes at least one of analysis functions including ontology relation analysis for validating class relation consistency on the ontology node, and the consistency on the integrated class structure, fact consistency analysis on the knowledge, and analysis on an implication relation, syntactic structure, classification, and incompleteness.

24. The method of claim 20, wherein the ontology object model analysis performs at least one of functional analyses including initially generating, maintaining, and managing a physical schema mapping table of the knowledge base, an ontology index mapping table, an ontology inference algorithm identifier table, a knowledge base service profile management table, a knowledge base service profile mapping table, and a user profile management table per knowledge base user grade.

25. An ontology-based knowledge modeling system comprising: a conceptual modeling unit for classifying a knowledge region of a

specific domain, performing detailed modeling on a conceptual detailed

domain within the classified knowledge region, and configuring a specific

domain knowledge model having the respective detailed models as a set; a logical modeling unit for configuring a schema-based logical model based on respective detailed schemas defined by referring to detailed models that correspond to the detailed schemas one by one from the set of the specific domain knowledge model of the conceptual modeling unit; and a physical modeling unit for configuring a physical knowledge reposit model by a detailed data repository for physically analyzing the schemas defined by respective detailed schemas in the logical modeling process, and a mediator for controlling an external interface of the detailed data repository.

26. The system of claim 25, wherein the respective models in the conceptual modeling unit and the logical modeling unit, and the respective models in the logical modeling unit and the physical modeling unit, are linked with each other, and are used as reference models, and lower models and higher models of the respective units are linked with each other and mapped in the horizontal direction.

27. The system of claim 25, wherein the physical modeling unit defines the detailed data repository and a corresponding interface as a single object, and builds a hierarchical object oriented model for linking with the external side of the object and for extension.

28. The system of claim 27, wherein the object oriented model of the physical modeling unit is realized as a knowledge service system which comprises an ontology-based knowledge base and a semantic network, and the knowledge service system comprises: a knowledge base build layer for storing the knowledge; an ontology-based knowledge base support layer including at least one of functions that include ontology access, ontology analysis, and ontology inference based on the ontology-based object model; an ontology platform describe layer including at least one of functions that include ontology mapping, ontology translation, ontology component visualization, and ontology driving; and a knowledge base link and management layer including at least one of functions that include ontology merging, ontology authoring, and integrated ontology management for the knowledge base.

29. The system of claim 28, wherein the knowledge base build layer comprises: a knowledge base for defining definitions of terminologies and relation establishment between the respective terminologies; and a web-based ontology for representing the knowledge base by using a network web-based format.