Development of Context Aware System based on Bayesian Network driven Context Reasoning Method and Ontology Context Modeling

Kwang-Eun Ko,Kwee-Bo Sim 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Network for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

Kwang-Eun Ko,Kwee-Bo Sim 한국지능시스템학회 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

Ko, Kwang-Eun,Sim, Kwee-Bo Korean Institute of Intelligent Systems 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

상황 온톨로지를 이용한 동적 의사결정시스템

김현우(Hyunwoo Kim),손미애(Mye Sohn),이현정(Hyun Jung Lee) 한국지능정보시스템학회 2011 지능정보연구 Vol.17 No.3

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker’s state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker’s personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker’s context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker’s personal case-base. We convince that the selected case should be the best case depending on context related to decision maker’s current status as well as decision maker’s requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn’t satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker’s requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

Ontology-based Context Modeling to Facilitate Reasoning in a Context-Aware System : A Case Study for the Smart Home

M. Robiul Hoque,M. Humayun Kabir,Keshav Thapa,Sung-Hyun Yang 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.9

A context-aware system provides services based on the current context of the environment and user activities. So, context management and reasoning in context-aware systems are important tasks. A formal context model based on ontology can play a vital role in facilitating reasoning by formally representing domain knowledge. This paper presents an ontology-based reusable generic context model for context-aware systems. This model provides a context vocabulary and structure for contexts and their semantics which are essential for reasoning. We evaluate the effectiveness of this model for both ontology and rule-based reasoning in the smart home domain and the result we obtain is promising.

중학생의 맥락적 도덕성에 관한 검증적 연구

이옥형 한국청소년학회 2009 청소년학연구 Vol.16 No.1

The purpose of this research was to examine the trend of contextual morality reasoning in Korean middle school students. The research questions were as follows. 1. Was there any difference between general morality reasoning and contextual morality reasoning? 2. Was there any difference among the relation context(parents, brothers and sisters, friends and teachers)? And was there any difference between the situation context(home and school). The subjects of this research were first and third grade Korean middle school students. 'The Moral Orientation Scale Using Dilemmas' and 'Contextual Morality Reasoning Scale' were used for this research . The statistical methods employed for data analysis were t-test, one-way ANOVA and scheffe test. The major finding of the research were as follows. 1. Care-oriented morality was higher than justice-oriented morality in contextual morality reasoning. Specially female students' care-oriented morality of contextual morality reasoning was higher than male students'. But there was no difference between justice-oriented morality and care-oriented morality of general morality reasoning. 2. Contextual morality reasoning was different among relation context. That is, justice-oriented morality of contextual morality reasoning was the highest at relation with teachers, the other hand it was the lowest with relation of friends. Care-oriented morality of contextual morality reasoning was almost same level high at relation with parents, brothers and sisters, friends. The other hand it was the lowest at relation with teachers. There was no difference between situation context(home and school) of contextual morality reasoning. 본 연구의 목적은 중학생의 일반적 도덕성과 맥락적 도덕성이 도덕지향성(정의지향성, 배려지향성)에 따라 다르게 나타나는지, 맥락적 도덕성은 맥락(관계맥락, 상황맥락)에 따라 다르게 나타나는지를 밝힘으로서 우리나라 중학생의 맥락적 도덕성에 대한 실증적 자료를 제공하는데 있다. 이를 위하여 중학교 1학년 학생과 3학년 학생 238명을 대상으로 Kohlberg 식의 가상적 사태의 ‘일반적 도덕지향성 검사’와 중학생이 경험하는 실제적 사태의 ‘맥락적 도덕지향성 검사’를 실시하였다. 자료 분석은 t-검증, 변량분석, 사후검증을 실시하였다. 연구결과 첫째, 일반적 도덕성은 정의지향성과 배려지향성 간에 차이가 없었으나, 맥락적 도덕성은 정의지향성보다 배려지향성을 더 높게 나타냈으며, 특히 여학생이 남학생보다 더 높은 배려지향성을 나타냈다. 둘째, 맥락적 도덕성의 도덕지향성은 관계맥락(부모·형제·친구·교사)에 따라 다르게 나타났다. 즉, 맥락적 도덕성의 정의지향성은 교사와의 관계에서 가장 높았으며, 친구와의 관계에서 가장 낮았다. 맥락적 도덕성의 배려지향성은 부모·형제·친구와의 관계에서 비슷하게 높았고, 교사와의 관계에서 가장 낮았다. 마지막으로 본 연구결과를 통하여 배려지향성이 맥락적 도덕성에서 두드러지게 나타남으로써 배려지향성 연구는 가상적 사태의 ‘일반적 도덕지향성 검사’보다 실제적 사태의 ‘맥락적 도덕지향성 검사’가 좀 더 적절함을 제안했으며, 성별 및 학년별 차이가 적게 나타난 결과 등에 대하여 논의하였다.

ARCHITECTURAL ANALYSIS OF CONTEXT-AWARE SYSTEMS IN PERVASIVE COMPUTING ENVIRONMENT

Udayan J., Divya,Kim, HyungSeok HCI Society of Korea 2013 한국HCI학회 논문지 Vol.8 No.1

Context aware systems are those systems that are aware about the environment and perform productive functions automatically by reducing human computer interactions(HCI). In this paper, we present common architecture principles of context-aware systems to explain the important aspects of context aware systems. Our study focuses on identifying common concepts in pervasive computing approaches, which allows us to devise common architecture principles that may be shared by many systems. The principles consists of context sensing, context modeling, context reasoning, context processing, communication modelling and resource discovery. Such an architecture style can support high degree of reusability among systems and allows for design flexibility, extensibility and adaptability among components that are independent of each other. We also propose a new architecture based on broker-centric middleware and using ontology reasoning mechanism together with an effective behavior based context agent that would be suitable for the design of context-aware architectures in future systems. We have evaluated the proposed architecture based on the design principles and have done an analyses on the different elements in context aware computing based on the presented system.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

고광은,심귀보 한국지능시스템학회 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

ARCHITECTURAL ANALYSIS OF CONTEXT-AWARE SYSTEMS IN PERVASIVE COMPUTING ENVIRONMENT

Divya Udayan J,HyungSeok Kim 한국HCI학회 2013 한국HCI학회 논문지 Vol.8 No.1

Context aware systems are those systems that are aware about the environment and perform productive functions automatically by reducing human computer interactions(HCI). In this paper, we present common architecture principles of context-aware systems to explain the important aspects of context aware systems. Our study focuses on identifying common concepts in pervasive computing approaches, which allows us to devise common architecture principles that may be shared by many systems. The principles consists of context sensing, context modeling, context reasoning, context processing, communication modelling and resource discovery. Such an architecture style can support high degree of reusability among systems and allows for design flexibility, extensibility and adaptability among components that are independent of each other. We also propose a new architecture based on broker-centric middleware and using ontology reasoning mechanism together with an effective behavior based context agent that would be suitable for the design of context-aware architectures in future systems. We have evaluated the proposed architecture based on the design principles and have done an analyses on the different elements in context aware computing based on the presented system.

온톨로지 기반 상황해석구조를 이용한 의도추론의 모호성 해결

이승철 ( Seung-chul Lee ),김치수 ( Chi-su Kim ),임재현 ( Jae-hyun Lim ) 한국인터넷정보학회 2007 인터넷정보학회논문지 Vol.8 No.5

온톨로지를 이용한 상황인식 시스템은 추론엔진의 도움을 받아 상황을 추론할 수 있다. 추론엔진의 도움을 받고, 추론규칙 문법에 맞는 추론규칙을 작성함으로써 기존 상황인식 시스템이 가진 추론의 모호성을 해결할 수 있다. 또한 추론 알고리즘을 프로그램으로부터 배제함으로써 새로운 상황에 보다 쉽게 적용할 수 있는 장점을 가진다. 본 논문에서는 온톨로지를 이용한 상황인식 시스템을 제안한다. 또한 온톨로지를 이용한 상황인식 시스템의 효용성을 확인하기 위해 가정을 대상으로 한 구현과 실험을 실시하였다. Context-Aware system using ontology is able to infer a context from help by reasoning engine. It can solve the ambiguity of intention reasoning of context-aware system as it is being made a reasoning rule followed reasoning grammar and being helped by reasoning engine. Also, it has a merit that is easy to apply to new environment by excluding reasoning algorithm from the program. In this paper, we are present context-aware system using ontology. We have tested and implemented it at home basis environment to verify of its effectiveness.