An Unified Representation of Context Knowledge Base for Mobile Context-Aware System

( Jang Seop Jeong ),( Dae Wook Bang ) 한국정보처리학회 2014 Journal of information processing systems Vol.10 No.4

To facilitate the implementation of a wide variety of context-aware applications based on mobile devices, general-purpose context-aware framework that applications can use by calling is needed. The context-aware framework is a middleware that performs the sensing, reasoning, and retrieving based on the knowledge base. The knowledge base must systematically represent the information required on the behavior of the context-aware framework, such as context information and reasoning information. It must also provide functions for storage and retrieval. To date, previous research on the representation of the context information have been carried out, but studies on the unified representation of the knowledge base has seen little progress. This study defines the knowledge base as the unified context information, and proposes the UniOWL, which can do a good job of representing it. UniOWL is based on OWL and represents the information that is necessary for the operation of the context-aware framework. Therefore, UniOWL greatly facilitates the implementation of the knowledge base on a context-aware framework.

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.

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.

A Study on an Object-orientation and Extensibility in Context-aware Systems

최종명,김익수 한국지식정보기술학회 2017 한국지식정보기술학회 논문지 Vol.12 No.2

There has been a lot of research on context-aware computing, but software extensibility in the development of those systems has not gotten much attention in spite of its importance in software engineering. In this paper, we introduce some extension requirements for context-aware systems, and identify four extension types for them: sensors, context inference algorithms, contexts, and context-aware services. For those extension requirements, we propose four extension mechanisms based on object-oriented technology: separation between abstraction and implementation of context, separation of context from sensors, modular and separate model for context-aware functions, and overloading model for context-aware functions. By adopting those mechanisms, developers or maintainers can add new sensors, context inference algorithms, contexts, or context-aware services without modifying the source code after deployment. Those mechanisms are all based on object-orientation. Our approach represents a context as a class, and context services as methods with context parameter. Context inference is a class with a method which understands sensor values and infers the current context from the values. This approach will reduce costs, time, and efforts in context-aware system maintenance which requires new context-aware features after deployment because it will increase the software reusability and extensibility. In this paper, we also specify a case study which shows how to extend a context-aware system with the extension requirements.

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.

Enabling Context-aware Smart Home with Semantic Web Technologies

Daqing Zhang,Tao Gu,Xiaohang Wang 한국과학기술원 인간친화 복지 로봇 시스템 연구센터 2005 International Journal of Assistive Robotics and Me Vol.6 No.4

  Context-awareness has emerged as a key enabling technology for future smart homes. In this paper, we propose a generic layered model (the Context Stack) to guide the context-aware system design. We investigate the use of Semantic Web technologies in context modeling and reasoning. A Web Ontology based context model (CONON) is defined to facilitate explicit context representation, semantic context sharing, and logic reasoning. We show how the use of logic reasoning enables context-aware services to deduce high-level, implicit context from low-level, explicit context. In particular, we integrate the temporal ontology into our ontology model to facilitate annotating and reasoning about temporal context information. Following the general layered model, we present an OSGi-based context-aware service architecture for smart homes. We also build the smart home prototype with context-aware services.

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.

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.

Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study

이연님,권오병 한국경영정보학회 2010 Asia Pacific Journal of Information Systems Vol.20 No.2

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users’ knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware person alized services. It is difficult to build users’ knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowsk...

Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study

Lee, Yon-Nim,Kwon, Oh-Byung The Korea Society of Management Information System 2010 Asia Pacific Journal of Information Systems Vol.20 No.2

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we out