KR100688087B1 - method for modeling context information using rules and ontology and context aware system - Google Patents

Abstract

1. TECHNICAL FIELD OF THE INVENTION

The present invention relates to a method of representing situation information using rules and ontology.

2. The technical problem to be solved by the invention

An object of the present invention is to provide a method of expressing contextual information using rules and ontology so that the system can use contextual information to recognize the surrounding situation in a ubiquitous environment.

3. Summary of Solution to Invention

The present invention relates to a method of expressing contextual information to be referred for context recognition, comprising: classifying a real world into a category having a common characteristic, and deriving a contextual information vocabulary (context conceptual vocabulary) from the classified category. In the step, defining (description) of the situations represented by the contextual information conceptual vocabulary, classifying the contextual information conceptual vocabulary according to the characteristics of the information with reference to the definition, modeling using the ontology in the step Modeling the information classified with the appropriate personality by ontology, mapping each conceptual vocabulary and the corresponding numerical section in the real world to the information classified with the personality suitable for modeling using the rules in the step; Step, creating a rule and a rule set using the result of said steps, said Comprising the step of creating a rule base to manage the principles and rules set.

4. Important uses of the invention

The present invention is used for a method of representing situation information using rules and ontology.

Rules, rule bases, ontology, ubiquitous, context-awareness, contextual information

Description

{Method for modeling context information using rules and ontology and context aware system}

1 is a configuration diagram of a general situation recognition processing system,

2 is a flowchart illustrating a method of expressing context information using rules and ontology according to the present invention;

Figure 3 is an exemplary rule for the temperature according to an embodiment of the present invention,

4 is a partial diagram of an ontology referred to by a rule base and a rule according to an embodiment of the present invention;

5 is a block diagram of a situation recognition system using rules and ontology according to an embodiment of the present invention.

The present invention relates to a method of presenting context information, and more particularly, by using rules and ontology to provide a basis for providing context information required by a system in order to recognize surrounding conditions in a ubiquitous environment. The present invention relates to a method of expressing context information.

In order to provide a wider range of services to users in a ubiquitous environment, the system must be able to be aware of the context of the user's surroundings. The main research trend of ubiquitous sensor network to recognize current situation is mainly focused on protocol of sensor network and infrastructure for operating sensor network. It is an important issue to establish a protocol for interoperation between sensors and interoperation between systems integrating them and infrastructure for integrated operation. However, studies to describe the physical environment necessary to actually operate the results presented in many of these studies are insufficient.

In order for the system to recognize the surrounding situation, first modeling of the situation information is necessary. However, as mentioned above, the existing studies mostly focus on the processing of the situation information itself, and do not provide a specific method for modeling the actual situation information. In addition, it is difficult to find an example of the contextual information actually modeled. In the rare case of modeled contextual information, only a small amount of contextual information is included for the verification of the system presented in the study, and even in this case, no specific method of expressing the contextual information is presented. All.

SUMMARY OF THE INVENTION The present invention has been proposed to solve the above problems, and an object thereof is to provide a method of expressing context information using rules and ontology so that the system can use context information to recognize a surrounding situation in a ubiquitous environment. .

In order for the system to recognize the surrounding situation, the actual environment (situation) must be expressed so that the system can recognize it, and in this process, the subjectivity of each individual who uses the system has to be considered. In addition, it is also difficult to uniformly express all surrounding situations as rules. Therefore, another object of the present invention is to efficiently represent the situation information by expressing the information that is difficult to be expressed by the rule by using the ontology and referencing the ontology when writing the rule, creating an objective reference rule base, and reflecting the factors of individual differences. The purpose of this paper is to provide a rule for creating an individual rule base and a situation information expression method using an ontology.

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.

Method for expressing the context information using the rules and ontology according to the present invention for achieving the above object, classifying the real world into a category having a common characteristic and deriving the context information conceptual vocabulary therefrom, the context information conceptual vocabulary Classifying the information represented by the information suitable for modeling using the ontology in which the state change is static based on the period of the state change and the information suitable for modeling using the dynamic rule in which the state change is performed. Modeling information suitable for modeling using the ontology classified in the step using ontology, modeling information suitable for modeling using the rule classified in the step using a rule, a rule for managing the rule Creating a base. When writing a rule, if there is information that cannot be expressed as a rule, the ontology information can be made available to the rule by mentioning the URI of the ontology to be referred to in the rule base.

In addition, the present invention proposes how a situation recognition system using the situation base can be constructed and operated when a knowledge base is constructed using a rulebase and ontology created using the contextual information expression method as described above. The situation recognition system using these rules and ontology recognizes the situation by analyzing the situation information collecting unit which collects or generates the situation information from the sensor, ontology and the web, and the situation information transmitted from the situation information collecting unit using the situation information reasoning machine. And a context information concept processing unit, and a context information concept processing unit storing a rule base and an ontology necessary for analyzing the situation. On the other hand, the situation information collection unit includes a situation information inference device, the situation information inference device is equipped with a rule engine software and ontology engine software.

The above-described contents of the present invention will become more apparent through the following detailed description with reference to the accompanying drawings, and thus, those skilled in the art to which the present invention pertains may easily implement the technical idea of the present invention. will be. In addition, in describing the present invention, when it is determined that the detailed description of the known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The general process for situational awareness processing is as follows. First, in order to recognize the surrounding situation, first, it is necessary to continuously collect the information change according to the change of the surrounding situation and interpret the collected information. Ambient information is mainly received through sensors, ontology and web. The collected collected information (data) is transmitted to a specific module, and the module receiving the information (data) interprets the information (data) through an internal operation.

1 is a block diagram of a general situation recognition processing system. As shown in FIG. 1, the general situation recognition processing system includes a situation information collection module 10, a situation information analysis module 20, an information expression medium 30, and an analysis result use module 40. The contextual information collecting module 10 obtains the surrounding contextual information (context data) and transmits the contextual information to the analysis module. The contextual information is collected through information gathering means such as a sensor. The contextual information analysis module 20 recognizes the current situation through inference from the transmitted context data, and the recognized contextual information is provided to the analysis result using module 40. In this case, in order for the contextual information analysis module to make an inference for recognizing the current situation, an information expression medium 30 that the interpretation module may refer to is required. The present invention relates to a situation information expression method in the information expression medium 30 as described above.

Context data collected through information gathering means such as sensors refers to data such as temperature and humidity, which are numerical values, which represent only a fraction of the situation and are used to make decisions necessary to perform the service (aware of the situation). In the following, the level of information contained in the data is very low. Therefore, proper processing of the collected context data must be preceded and this process is defined as context conceptualization. That is, the context conceptualization refers to a process of converting data that simply describes or indicates surrounding situations collected from various sensors and information repositories into situation information that can be used in making a decision to perform a service. Hereinafter, the terms 'context information' and 'context' are described in the same meaning, and when a distinction is required, the terms are used according to the context.

2 is a flowchart illustrating a method of expressing situation information using rules and ontology according to the present invention.

Referring to Figure 2 describes a method of expressing the situation information using the rules and ontology according to the present invention.

First, the real world is classified into categories having common characteristics (step S110). The scope covered in the present invention includes all categories other than environment, temperature, humidity, noise, air pollution, illuminance, traffic, weather, people, relationships between people, devices, and spaces.

In step S120, contextual conceptual vocabulary (context conceptual vocabulary) for deriving a real situation is derived from the classified category. Situational information conceptual vocabulary refers to a word that implies a situation in the real world. Conceptual vocabularies describe real situations and must be able to provide information about physical situations by themselves. For example, for temperature categories, "Sizzling", "Hot", "Warm", "Cool", "Cold", "Freezing" Very cold). " Contextual vocabulary can be defined irrespective of region, season, personal preference, etc., and therefore can be used in common in any situation. (However, specific context data values mapped to context conceptual vocabularies may be affected by regions, seasons, personal preferences, etc., which may be referred to when creating a rule base described below.)

Conceptual vocabulary is divided into Primary Concept vocabulary and Composite Concept vocabulary. The basic conceptual vocabulary is a conceptual vocabulary for situational awareness that can be directly derived from the raw context data transmitted through the sensor. These basic vocabularies are defined by only relatively objective facts that correspond directly to the current physical environment. On the other hand, the compound concept vocabulary refers to a combination between the basic concept vocabulary, a combination of the basic concept vocabulary and the complex concept vocabulary, or a combination between the complex concept vocabulary, and these complex vocabularies can express more complex contextual information.

In step S130, for each situation information conceptual vocabulary derived in step S120, it is defined (described) which situation the derived situation information conceptual vocabulary represents. Such a definition may be described as an ontology using OWL (Web Ontology Language), or may be managed in a general database. This step aims to objectively express the situation represented by the conceptual vocabulary by reducing the difference in perception that can occur for each person.

Table 1 and Table 2 below show the derived concept information vocabulary and how to define it. Table 1 shows the basic concept vocabulary and its situation definition. Table 2 shows the complex concept vocabulary and its situation definition. Since the basic conceptual vocabularies shown in Table 1 are derived from a single raw data acquired from sensors, ontology and web, only the context definitions for the basic conceptual vocabularies are described. On the other hand, the compound concept vocabulary shown in Table 2 additionally shows the basic concept or the compound concept combined in addition to the situation definition.

 Primitive Concept  Context Definition  Basic concepts 1  This situation is ...  Basic concepts 2  This situation is ...  Basic concepts 3  This situation is ...  .....  .....

Composite Concept Related Concept Context Definition Compound concept 1 Basic concepts 1, basic concepts 2 This situation is ... Compound concept 2 Basic Concepts 1, Composite Concepts 1 This situation is ... Composite concept 3 Compound Concept 1, Compound Concept 2 This situation is ... ..... ..... .....

In step S140, the information (conceptual vocabularies) to be modeled is classified according to the nature of the information with reference to the contents described in step S130. Information here includes all information that requires modeling to be referenced in order to interpret contextual information. The purpose of classifying information to be modeled is to distinguish between information suitable for modeling and information suitable for ontology using rules. Classification criteria include the period of state change (dynamic or static) and whether the information has a hierarchical structure. In other words, in the case of information of the nature that provides dynamic situational information with a short cycle and changes frequently, the situation information is modeled using a rule. On the other hand, for information that has a hierarchical structure, strong descriptive nature, no periodic state changes, or relatively long change cycles, the information is modeled by using ontology.

In step S150, modeling using the ontology, which is classified in step S140, is modeled as an ontology of information (information having a relatively long period and hierarchical structure) having suitable characteristics. In other words, information that is hard to be expressed by rules is modeled using ontology. The ontology can be created using OWL (Web Ontology Language) proposed by the World Wide Web Consortium (W3C). Information that is difficult to express in rules includes people, devices (including sensors), spaces, regions, and environmental information. Such information is difficult to be expressed as a rule as information to be described about general matters rather than a specific situation.

In addition, if specific context information is related to information that should be described about general matters, it can be modeled by ontology. For example, specific environmental information such as air pollutants can be described as simple facts and related to sensor information, so they can be modeled as ontology rather than as a rule.

Since the rulebase described below specifies the criteria for judgment according to a specific situation as a rule, information beyond these criteria should also be modeled by ontology. For example, the ontology describing the sensor includes the type of the sensor, the location where the sensor is located, and the like. That is, it is more natural to use the ontology for description (description) rather than the rules for judgment of the information about the equipment such as the sensor.

When information is represented (modeled) in ontology, since other systems can refer to the information, it is easy to integrate with other systems in the future. Therefore, it may be advantageous to model information on which ontology is expected to be used.

In step S160, the conceptual vocabularies and specific numerical sections corresponding to the conceptual vocabularies are mapped to the information classified as the characteristics to be modeled using the rules in step S140. The conceptual vocabulary defined (described) in step S130 should exist in pairs with the context data values of the corresponding situation. For example, if the context data value is 35 degrees or more, the corresponding conceptual vocabulary can be expected to be “sizzling” (very hot).

As mentioned in step S120, the conceptual vocabulary can be defined irrespective of region, season, personal preference, etc., and thus can be commonly used in any situation. On the other hand, specific context data values mapped to conceptual vocabularies may be set by referring to standards (for example, Korean environmental standards) that can be easily agreed to by the general public, or reflect local, seasonal, or personal preferences. have. In the case of reflecting personal preferences as mentioned above, these points should be referred to when creating a rule base.

In step S170, using the results of the above steps, a rule and a rule set are prepared for information of a nature to be modeled as a rule. The conceptual vocabulary described in the rule can be divided into two kinds of basic vocabulary and complex conceptual vocabulary as mentioned above, and the amount of information of the rule can vary according to each conceptual vocabulary. Rulesets, on the other hand, are logical units that manage rules of similar nature that play the same role. In one rule set, conceptual vocabularies that can be derived from context data collected from a sensor are defined in the form of various rules.

In writing rules, information that is difficult to express with rules can be written by referring to the ontology. Specifically, when there is information that is difficult to express by rule, by referring to the URI (Uniform Resource Identifier) of the ontology to be referred, it is possible to take advantage of each information expression method.

3 are rules for temperature in accordance with one embodiment of the present invention. According to the rules shown in FIG. 3, the concept of Hot is derived when the temperature transmitted from the sensor exceeds 25 degrees and is 30 degrees or less, and the concept of Warm is derived when the temperature exceeds 20 degrees and is 25 degrees or less. do. A device used as a prefix indicates a URI (Uniform Resource Identifier) of device.owl so that information about an external device (sensor) can be referred to in a rule.

The rules created in step 170 are managed by the rulebase. The rulebase is created according to the rulebase creation instructions using the results of the above steps S110, S120, S130, S140, S150, S160, and S170 (step 180).

The rulebase creation guidelines specify that all rules in a rulebase should be created from the same point of view. In addition, it corrects the change of situation that may occur according to region, season, time, and individual difference, and decides to provide the same judgment standard and interpretation standard in judging and interpreting the situation using rule base. In addition, the rulebase preparation guidelines include declaration of prefix or namespace for ontology reference, declaration of rule set which is a combination of rules, management of rules through it, guidelines for declaring rule sets and rule names.

In developing the rulebase according to the rulebase preparation guidelines as described above, in order to correct changes according to various situations, various situation factors that may affect the recognition of situations are classified according to certain criteria, and the classified criteria are classified. Create a rule base for each situation. For example, regional factors can be classified into climate zones, seasonal factors can be classified into 12 seasons, and time of day can be classified into 9, and these criteria can be classified according to regional, seasonal, and temporal factors. It provides a foundation for writing a base. In addition, these classified criteria can help to make consistent interpretation and judgment at the stage of using the rulebase.

The standard rulebase prepared as above does not consider individual differences. This is because when the rulebase is created for each individual by reflecting individual differences in the baseline rulebase creation, there may be difficulty in managing the rulebase due to the increase in the number of rules to be managed. Therefore, first create a baseline rulebase, and then create individual rulebases by reflecting each individual difference factor in the baseline rulebase. For example, reflecting individual differences at the time of deriving a situation concept based on a reference rule base makes it possible to create an individual rule base that reflects individual differences relatively easily.

In addition, by declaring prefix and namespace when writing rule base, URI can not be used as a whole when writing rule base, and the meaning of relevant vocabulary should be clarified to make the reasoning in the reasoning engine to be explained later. You can prevent duplication. For example, if "prefix deviceContext = http: // ~~", "namespace is http: // AAA" is declared, the prefix "deviceContext" appears before the predicate name in the rulebase. The predicate name without the prefix is executed with the URI declared in the namespace.

On the other hand, as an example of the declaration guideline of a rule set and a rule name, the case where the rule set and the rule generate | occur | produces the combination of the kind, timing, conceptual vocabulary, etc. which the context wants to represent is mentioned. If you have a rule set for "midsummer / afternoon / temperature" and there are rules for "Sizzling" and "Hot", then the rule set can be named "PrimitiveTemperatureforMidSummerNoon" and the rule is " TemperatureSizzling "and" TemperatureHot "can be named (see Figure 4).

4 is a diagram illustrating a rulebase and a part of the ontology referred to by a rule according to an embodiment of the present invention. More specifically, the rule base shown in FIG. 4 includes a set of rules for managing rules regarding the temperature of midday noon, and the presented rule is for "Sizzliing". On the other hand, deviceContext is an ontology that describes information about a device, and includes information such as the type and attribute of the device. In FIG. 4, the proposed rule TemperatureSizzling receives a temperature value from a sensor that is a corresponding device (Temperature (? Sensor,? Temperaturevalue)), and infers the position of the sensor from sensor information described by ontology (deviceContext: positionedAt (? sensor,? space), when the input temperature is more than 30 degrees, the conclusion is that the 'space where the sensor is located (for example, the room) is very hot' (cxt: Sizzling (? In the above process, as illustrated in FIG. 4, if the URI of the ontology to be referred to in the rulebase is described (A) and the vocabulary in the ontology is described in the rule (B), the rule engine will be described below. Through the interworking of the ontology engine and the processing of the corresponding part is made.

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.

5 is a block diagram of a situation recognition system using rules and ontology according to an embodiment of the present invention.

The situation recognition system illustrated in FIG. 5 includes a situation information collecting unit 100, a situation information concept processing unit 200, and a database unit 400, and the situation information concept processing unit 200 uses the situation information reasoning unit 300. It is included.

The contextual information collecting unit 100 is composed of various sensors, ontology, etc. which are geographically dispersed. The contextual information collecting unit 100 collects or generates contextual information from a plurality of distributed sensors or ontology and transmits the contextual information to the contextual information concept processing unit 200.

The contextual information concept processing unit 200 includes a contextual information reasoner 300, and the contextual information reasoner 300 includes a rule engine software 310 and an ontology engine software 320. The situation information concept processing unit 200 represents the current situation using the situation information (raw situation information or processed situation information) received from the situation information collecting unit 100 using a rule base or ontology in the database unit 400. Convert to concept Specifically, the contextual information concept processing unit 200 refers to the rule base 410 in the database unit 400 to process the rules related to the contextual information, and the referenced rulebase is rule engine software located in the contextual information reasoning machine. Is processed by 310. In addition, when the contextual information is to be represented using the ontology, the ontology 420 in the database unit 400 is referred to, and the ontology referred to is used by the ontology engine software 320.

When the rule engine software 310 refers to the ontology in processing the referenced rule base, the rule engine software 310 interlocks with the ontology engine software 320 to establish an ontology in the database 400. By referring to 420, the ontology information referred to by the rule is processed.

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.

The present invention as described above, by presenting a specific method for modeling the context information using rules and ontologies, to provide the context information required for the various systems with a digital-based processor in the ubiquitous environment to recognize the surrounding situation Provide a foundation to do so. This modeling of contextual information is an essential procedure for context-awareness and can be effectively used in the future in providing substantial services.

According to the present invention, information that is difficult to be expressed by a rule is expressed by using an ontology, and when the rule requires it, the ontology information is referred to so that the situation information can be effectively expressed while taking advantage of each information expression method. Do it. In addition, the use of the universal ontology as described above facilitates integration with other systems, and can also be added to the future using new ontologies that can occur in the future, allowing flexibility to respond to future changes.

In addition, the present invention can solve the localization problem by properly combining the rulebase, and can provide the situation information considering the subjectivity of each individual by adjusting the numerical values corresponding to the context information.

Claims (10)

(A) classifying the real world into categories having common characteristics and deriving contextual information vocabulary from them; (B) Information suitable for modeling the information represented by the contextual information conceptual vocabulary using ontologies where the state change is static based on the cycle of state change and information suitable for modeling the state change using dynamic rules Categorizing into; (C) modeling using ontology information suitable for modeling using the ontology classified in step (b); (D) modeling information suitable for modeling using the rules classified in step (b) using the rule; (E) creating a rule base to manage the rules; Situation information representation method using a rule and an ontology, characterized in that comprises a. The method of claim 1, The contextual information vocabulary It consists of a complex conceptual vocabulary consisting of a combination of basic conceptual vocabulary that can be directly derived from raw context data and the basic conceptual vocabulary. The complex conceptual vocabulary may be made of a combination of the basic conceptual vocabulary and another complex conceptual vocabulary or a combination of different complex conceptual vocabularies. Situation information expression method using a rule and ontology characterized in that. The method of claim 1, And defining a situation represented by the derived contextual information conceptual vocabulary, The information represented by the conceptual vocabulary of contextual information is classified with reference to the above-defined contents. Situation Information Representation Method using Rules and Ontologies. delete The method of claim 1, Information classified as suitable for modeling using the rule may be modeled as a rule by mapping a conceptual vocabulary of each information and a corresponding numerical section in the real world. Situation Information Representation Method using Rules and Ontologies. The method according to claim 1 or 5, When ontology reference is required in modeling using the rule, the ontology information can be used in the rule by declaring a URI (Uniform Resource Identifier) of the ontology to be referred to in the rule base. Situation Information Representation Method using Rules and Ontologies. The method of claim 1, The rulebase is created according to the rulebase creation guidelines. The rulebase preparation guideline makes all the rules included in the rulebase from the same point of view, and corrects the situation change that can be caused by various factors such as region, time, individual difference, etc. Characterized in that it is determined to provide the same criteria and interpretation criteria Situation Information Representation Method using Rules and Ontologies. The method of claim 7, wherein The steps to create a rulebase Creating a baseline rulebase according to the rulebase creation guideline above; And a step of creating an individual rule base by reflecting the individual difference factor in the reference rule base. Situation Information Representation Method using Rules and Ontologies. A situation information collection unit for collecting or generating situation information from a sensor, an ontology and the web; Classify the real world into categories with common characteristics, derive contextual vocabulary from contextual information, and model the information represented by the contextual informational vocabulary by modeling the state change using dynamic rules. After classifying the information and the state change into the information of the nature to be modeled using the static ontology, the information of the nature to be modeled using the ontology is modeled by the ontology and the information of the nature to be modeled using the rules For modeling, we map the numerical section corresponding to each piece of information and model it as a rule, manage these rules, and create a rulebase that can refer to the ontology if needed. A database unit for storing a rule base and an ontology created by the context information expression method using rules and ontology; It has regular engine software and ontology engine software. When the context information collection unit receives the context information, the context information concept processing unit recognizes the situation by processing the rule base or ontology in the database unit related to the context information input through the rule engine software and the ontology engine software. Situational awareness system using rules and ontology, characterized in that made. The method of claim 9, When the rule engine refers to the ontology when the rule engine software processes the rule base referenced from the database unit, the ontology information is processed by referring to the ontology in the database unit in conjunction with the ontology engine software. Context awareness system using rules and ontology.

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