KR100941969B1 - Apparatus for processing the dynamic contexts - Google Patents

Abstract

1. TECHNICAL FIELD OF THE INVENTION

The present invention relates to a dynamic context processing apparatus.

2. The technical problem to be solved by the invention

The present invention provides a dynamic context processing apparatus for temporarily generating an instance and a query of an ontology corresponding to the dynamic context and performing the corresponding inference in order to perform dynamic inference with respect to various kinds of dynamic contexts obtained from a plurality of sensors. The purpose is to provide.

3. Summary of Solution to Invention

According to an aspect of the present invention, there is provided a context processing apparatus, comprising: a dynamic context representation medium storage unit having an n-triple (n-triple) representation medium corresponding to an ontology schema model; A dynamic context definition unit for determining a dynamic context received from the outside as an ontology model using the n-triple expression medium; A query definition unit defining a query model used to recognize a context determined by the dynamic context definition unit, wherein the query model includes a fact about the dynamic context and a corresponding query; And a dynamic context processor for performing inference determination based on the inference rule using the ontology model and the query model, and removing facts included in the query model used for the inference determination.

4. Important uses of the invention

The present invention is used in the context processing / reasoning field.

Dynamic context, inference, query, ontology

Description

Apparatus for processing the dynamic contexts}

1 is a configuration diagram of an embodiment of a dynamic context processing apparatus according to the present invention;

FIG. 2 is a detailed block diagram of an embodiment of the dynamic context processor of FIG. 1;

FIG. 3 is a diagram for explaining an ontology instance for dynamic context processing according to the present invention.

4 is an exemplary diagram for illustrating an inference rule for dynamic context processing according to the present invention.

5 is a diagram illustrating an embodiment of a query for dynamic context processing according to the present invention;

6 is a flowchart of an embodiment of a dynamic context processing method according to the present invention.

* Explanation of symbols on the main parts of the drawing

10: dynamic context expression media storage

11: dynamic context definition

12: query definition section

13: dynamic context processor

21: query engine 22: instance generator

23: ontology repository 24: deduction rule repository

25: Ontology Engine

The present invention relates to a context processing device, and more particularly, to temporarily generate an instance and a query of an ontology corresponding to the dynamic context in order to perform dynamic inference on various kinds of dynamic contexts obtained from a plurality of sensors. A dynamic context processing apparatus for performing the inference.

Recently, in ubiquitous, for example, home networking, telematics, etc., a service that detects a user's current situation and infers optimal information is being spotlighted, and a context processing technique and a reasoning technique are applied to such a service.

On the other hand, as the world becomes more complex, users face various environments, and the contexts representing these situations must also be collected and acquired from many different types of sensors. It has a dynamic characteristic.

On the other hand, in inference system, it is important to recognize the user's situation effectively by processing various kinds of dynamic contexts obtained from a plurality of sensors. That's the key to improving system performance.

As a related art related to the inference system introduced above, Korean Patent Application Publication No. 2007-1319 (name of the invention: "Development of inference technique of inference engine for providing context-aware intelligent service in ubiquitous environment") [hereinafter, " Prior Art 1 "] and Republic of Korea Patent No. 707671 (name of the invention:" a reasoning apparatus and method for providing context-based adaptive service based on multi-home network environment ") [hereinafter, referred to as" prior art 2 " ].

The prior art 1 proposes an inference technique for providing a home network service according to a static pattern or a dynamic pattern based on a user profile and a user location, and the prior art 2 based on a user profile, a user location, and a user behavior pattern. In order to provide a situation-adaptive service, a thread is created so that the service can be processed in parallel.

However, the context processing method proposed by the prior art including the above-described prior arts, adds / remove routines provided by the inference engine in processing various types of dynamic contexts obtained from a plurality of sensors. By doing so, the system load and the resulting service delays caused by the addition / deletion routines required for numerous dynamic contexts for many users at the same time.

Therefore, there is an urgent need for a technique capable of performing dynamic inference by processing various types of dynamic contexts obtained from a plurality of sensors, regardless of system resources of limited resources without affecting or processing dynamic contexts of other users. .

The present invention has been proposed to solve the above problems and to meet the above demands. In order to perform dynamic inference on various kinds of dynamic contexts obtained from a plurality of sensors, an ontology corresponding to the dynamic context may be used. Its purpose is to provide a dynamic context processing device that temporarily creates instances and queries to perform inference.

Other objects and advantages of the present invention can be understood by the following description, and will be more clearly understood by the embodiments of the present invention. Also, it will be readily appreciated that the objects and advantages of the present invention may be realized by the means and combinations thereof indicated in the claims.

An apparatus of the present invention for achieving the above object is, in the context processing apparatus, a dynamic context in which an n-triple (n-triple) expression medium corresponding to an ontology schema model is stored. Expression media repository; A dynamic context definition unit for determining a dynamic context received from the outside as an ontology model using the n-triple expression medium; A query definition unit defining a query model used to recognize a context determined by the dynamic context definition unit, wherein the query model includes a fact about the dynamic context and a corresponding query; And a dynamic context processor for performing inference determination based on the inference rule using the ontology model and the query model, and removing facts included in the query model used for the inference determination.

In addition, the dynamic context processing unit in the apparatus of the present invention, the query engine for separating the facts and the query about the context from the query model determined by the query definition unit for performing an inference query to the ontology engine; An instance generation unit for generating an ontology instance corresponding to a fact separated from the query engine, and temporarily adding and storing the ontology instance in an ontology repository; And based on the corresponding inference rule stored in the inference rule store, by using a query separated from the query engine, on the ontology instance corresponding to the fact stored in the ontology store, and performs the inference decision. It includes the ontology engine for deleting the ontology instance used in.

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The foregoing and other objects, features and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings, in which: There will be. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a configuration diagram of an apparatus for processing a dynamic context according to the present invention, and FIG. 2 is a detailed configuration diagram of an embodiment of the dynamic context processor of FIG. 1.

As shown in FIG. 1, the apparatus for processing a dynamic context according to the present invention includes a dynamic context expression medium storage 10, a dynamic context defining unit 11, a query defining unit 12, and a dynamic context processing unit 13. do.

The dynamic context processor 13 includes a query engine 21, an instance generator 22, an ontology store 23, an inference rule store 24, and an ontology engine 25.

Meanwhile, a plurality of sensors 50 are provided for collecting and acquiring a dynamic context corresponding to the current situation of the user.

In the present invention, in order to perform dynamic inference on various types of dynamic contexts obtained from the plurality of sensors 50, an ontology model and a query model corresponding to the dynamic context are temporarily generated to perform inference based on the corresponding inference rule. do.

That is, in the present invention, various types of dynamic contexts obtained by the plurality of sensors 50 are defined as ontology models, and the dynamic contexts are temporarily stored as ontology instances, and a query model including the dynamic contexts is defined to define the ontology model. Applied inference rules are applied to temporary ontology instances to determine inference information appropriate to the user's situation.

Also, in the present invention, the temporary ontology instance corresponding to the dynamic context used for the inference determination is deleted after the inference process is used.

For example, in order to provide a user with services regarding a user's location, current time (working hours, lunch break, etc.), weather conditions, traffic conditions, etc. in a ubiquitous environment, contexts generated in various domains need to be conceptually defined. .

In addition, various types of dynamic contexts obtained from a plurality of sensors are data required for reimbursement determination related to a user's location, current time, weather, traffic, and the like. For example, a context obtained from a location sensor represents a user location as a coordinate. In other words, it is not possible to perform inferences about the user situation through coordinates in providing the appropriate service for the user location in the inference engine. For example, if the inference engine receives (1234567, 1234555) coordinate information from the position sensor, it must be able to infer specific service information to be provided when the user is located in the living room after determining that the user is located in the living room. .

To this end, in the present invention, the dynamic context is defined based on the ontology model so that the inference engine can recognize various kinds of dynamic contexts obtained from a plurality of sensors.

Then, each component of the dynamic context processing apparatus proposed by the present invention will be described in detail below.

The dynamic context expression medium storage 10 stores an n-triple (n-triple) expression medium corresponding to the ontology schema model specified in the OWL-DL (Description Logic) language. have. Here, n-triple includes "subject", "predicate" and "object". The dynamic context expression medium is a representation method for conceptually defining contexts generated in various domains. For example, in the dynamic context expression medium storage 10, conceptual information about weather, location, traffic, and the like is defined, and the dynamic context definition unit 11 corresponds to characteristics of a corresponding domain in a dynamically generated context. Allows you to define a context.

The dynamic context definition unit 11 defines a context input from an external sensor 50 in accordance with an ontology model on the OWL-DL language using an n-triple expression medium stored in the dynamic context expression medium storage 10. . Here, the dynamic context definition unit 11 uses a dot ["."] As the n-triple delimiter. For example, the n-triple expression medium includes a dot ["."] As an object identifier. The context defined for the OWL-DL language can be recognized and processed as an ontology model on the inference engine. For example, when the current sensor acquires the current road speed and traffic information as a dynamic context, the dynamic context definition unit 11 defines the dynamic context using an n-triple expression medium in accordance with the traffic situation awareness ontology model. do.

The query defining unit 12 defines a query model to be used to recognize a context defined by the n-triple expression medium in the dynamic context defining unit 11. For example, when the current road speed and traffic volume information is obtained from the traffic sensor, the query defining unit 12 generates a traffic situation awareness query model including an expression for querying the current traffic situation for this dynamic context. define. That is, such a traffic situation awareness query model includes an ontology model corresponding to a context that indicates a situation where a user is in a query and a query that queries the current traffic situation.

The dynamic context processor 13 uses the ontology model corresponding to the context defined by the dynamic context definer 11 and the query model defined by the query definer 12 to perform inference determination based on the corresponding inference rule. In addition, the dynamic context processing unit 13 deletes the temporary ontology instance generated corresponding to the dynamic context after the inference decision. The dynamic context processor 13 performs an inference determination process based on the inference engine based on the OWL-DL. Then, such a dynamic context processor 13 will be described in more detail with reference to FIG. 3.

The query engine 21 of the dynamic context processor 13 separates the fact and the query about the context from the query model defined by the query definer 12 and performs an inferential query on the ontology engine 25. Here, the query uses "SPARQL" [RDF Query Language] standardized as an inference engine query by "W3C".

That is, the query model includes a query for querying the user situation and the user context, and the query engine 21 extracts the query from the query model and extracts the fact from the context included in the query model. Extract it and separate it into a query and a fact.

Then, the query engine 21 transmits the fact separated from the query model to the instance generator 22 to be used as temporary instance information of the ontology store 23, and the query separated from the query model. Is sent to the ontology engine 25 to store the inference query, that is, the fact that the ontology engine 25 is temporarily additionally stored as an ontology instance in the ontology store 23 in the inference rule store 24. Make inference decisions based on the inference rules in place.

The instance generator 22 of the dynamic context processor 13 generates an ontology instance corresponding to a fact separated from the query engine 21, and temporarily adds and stores the ontology repository 23 in the ontology store 23. In this case, since the fact is defined as the n-triple expression medium according to the ontology schema by the dynamic context definition unit 11, the fact can be generated and stored as an ontology instance.

The ontology engine 25 of the dynamic context processor 13 separates a query separated by the query engine 21 for an ontology instance corresponding to a fact about the context that is temporarily stored in an ontology repository 23. To make an inference decision based on the corresponding inference rule stored in the inference rule store 24. Then, the ontology engine 25 deletes the ontology instance corresponding to the fact about the context that was temporarily stored in the ontology repository 23 after performing the inference decision.

3 is a diagram illustrating an embodiment of an ontology instance for dynamic context processing according to the present invention.

3 illustrates an ontology instance for use in recognizing a time situation when the context acquired by the external sensor 50 is time information, and specifically, it is a fact of recognizing a time type over time. .

4 is a diagram for explaining an embodiment of inference rules for dynamic context processing according to the present invention.

In FIG. 4, when the context acquired by the external sensor 50 is time information, an inference rule for use in time situation recognition is illustrated. Specifically, the current time is stored in the ontology store 24. It is an inference rule that derives the current time type from the time ontology instance of FIG. 3.

5 is a diagram illustrating an embodiment of a query for dynamic context processing according to the present invention.

In FIG. 5, when the context acquired by the external sensor 50 is time information, time for an event generated by an external sensor is defined as a context, and a type for determining the type of time at which the event occurs during an inferred query is performed. Query.

6 is a flowchart of an embodiment of a dynamic context processing method according to the present invention. Hereinafter, the n-triple expression medium corresponding to the ontology schema model specified in the OWL-DL (Description Logic) language is stored in the dynamic context expression medium storage 10, and the dynamic context is input from an external sensor 50. The flow will be described for the case.

When a dynamic context is input from the external sensor 50 (601), the dynamic context is defined as an ontology model using the n-triple expression medium (602).

In operation 603, a query model used to recognize the defined context is defined.

Then, the fact and query about the context are separated from the defined query model (604).

Thereafter, an ontology instance corresponding to the separated fact is generated and temporarily added to and stored in the ontology repository 23 (605).

Then, the inferred decision is made based on the corresponding inference rule stored in the inference rule store 24 using the separated query for the ontology instance corresponding to the fact stored in the ontology store 23. (606).

Thereafter (after performing the inference decision), the ontology instance corresponding to the fact about the context stored in the ontology store 23 is deleted (607).

As described above, the method of the present invention may be implemented as a program and stored in a recording medium (CD-ROM, RAM, ROM, floppy disk, hard disk, magneto-optical disk, etc.) in a computer-readable form. Since this process can be easily implemented by those skilled in the art will not be described in more detail.

The present invention described above is capable of various substitutions, modifications, and changes without departing from the technical spirit of the present invention for those skilled in the art to which the present invention pertains. It is not limited by the drawings.

As described above, the present invention has an effect of performing dynamic inference with respect to various kinds of dynamic contexts obtained from a plurality of sensors.

In addition, the present invention can process dynamic contexts regardless of system performance of limited resources without affecting or affecting dynamic context processing for other users, and thus a system for processing a large number of dynamic contexts for a large number of users at the same time. It has the effect of solving the load and service delay problem.

In addition, the present invention defines various types of dynamic contexts obtained from a plurality of sensors as ontology models, thereby enabling the inference engine to recognize dynamic contexts, and to various situational changes generated from various domains in the ubiquitous environment. It has the effect of being flexible.

Claims (11)

In the context processing apparatus, A dynamic context expression medium storage including an n-triple (n-triple) expression medium corresponding to the ontology schema model; A dynamic context definition unit for determining a dynamic context received from the outside as an ontology model using the n-triple expression medium; A query definition unit defining a query model used to recognize a context determined by the dynamic context definition unit, wherein the query model includes a fact about the dynamic context and a corresponding query; And A dynamic context processor for performing inference determination based on the inference rule using the ontology model and the query model, and removing facts included in the query model used for the inference determination. Dynamic context processing device comprising a. The method of claim 1, The dynamic context processing unit, A query engine that separates a fact and a query about a context from a query model determined by the query definition unit and performs an inference query with an ontology engine; An instance generation unit for generating an ontology instance corresponding to a fact separated from the query engine, and temporarily adding and storing the ontology instance in an ontology repository; And An inference decision is performed on the ontology instance corresponding to the fact stored in the ontology store, based on the corresponding inference rule stored in the inference rule store using a query separated from the query engine, The ontology engine to delete the ontology instance used Dynamic context processing device comprising a. delete The method according to claim 1 or 2, The n-triple expression medium includes an ontology schema model specified in an OWL-DL (Description Logic) language. The method according to claim 1 or 2, The n-triple expression medium includes a dot ["."] As an object identifier. The method according to claim 1 or 2, The query model includes a context for querying a user context and a user context. The method of claim 6, And the query includes " SPARQL " [RDF Query Language]. delete delete delete delete

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