• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.1
• /
• pp.24-34
• /
• 2007

Since Context Driven Component model is based on the idea that a context-aware application consists of the components that are context sensitive and the components that do not depend on the context, it divides the context sensitive part into components according to which context information they are related to. The model supports the scalability of context information by building an application through composing Context Driven Components. Furthermore, it solves the embeddedness of context information inside the application logic. To show the contributions of the model, this paper applies it to Call-forwarding application, and analyses how the model supports the scalability and the embeddedness.

• Korean Journal of Cognitive Science
• /
• v.2 no.2
• /
• pp.279-307
• /
• 1990

The present research inverstigates the nature of contextual effects on pronoun reference resolution during text comprehesion.Through three experiments,this research examines how various contextuall informations influence on reference resolution and interact with syntactic variables.In experiment 1,the local context was controlled by biasing the pronoun-sentence context towards a certain preceding referent.The lexical decision time and the forced choice time for the correct referent were measured.The results showed that the local contexts have clear effect on reference resolution.The effects of syntactic ambiguity were also observed though the local context was biased towards a certain referent noun.In experiment 2,the global context effect was examined by introducing the text-thematic context in a preceding sentence while keeping the following pronoun-sentence context neutral.The results showed that the global thematic context bias towards a subject or object in a preceding sentence entails a faster response time than the thematically neutral context.In experiment 3,another aspects of context effects were inverstigated by manipulating the consistency of the preceding thematic context with the following pronoun-sentence context.The results showed that the lexical decision responses and forced referent choice responses were faster when the prethematic context and the post-anaphoric context match than when they mismatch.In sum,the overall results of three experiments of this research indicates that context has a clear effect on pronoun reference resolution during text comprehension.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.463-468
• /
• 2011

Context prediction methods have been developed in two ways - one is a prediction for discrete context and the other is for continuous context. As most of the prediction methods have been used with prediction algorithms in specific domains suitable to the environment and characteristics of contexts, it is difficult to conduct a prediction for a user's context which is based on various environments and characteristics. This study suggests a context prediction method available for both discrete and continuous contexts without being limited to the characteristics of a specific domain or context. For this, we conducted a context prediction based on sequence matching by generating sequences from contexts in consideration of association rules between context attributes and by applying variable weights according to each context attribute. Simulations for discrete and continuous contexts were conducted to evaluate proposed methods and the results showed that the methods produced a similar performance to existing prediction methods with a prediction accuracy of 80.12% in discrete context and 81.43% in continuous context.

• Journal of The Korean Association For Science Education
• /
• v.23 no.1
• /
• pp.47-56
• /
• 2003

The present study was carried out to analyse the frequency(%) for five kinds of inquiry context elements for six kinds of the high school science textbooks in the 7th curriculum. All the elements was classified into three process achievement level such as the basic, supplementary and further level introduced firstly in the 7th curriculum. Five elements of the inquiry context categories appeared as pure scientific context(61.8%), everyday context(22.2%), natural environmental context(7.7%), techno-industrial context(5.9%), and social context(2.4%) in the basic, supplementary and further level. Social context wasn't appeared in the supplementary level. In five elements of inquiry context, total elements appeared 7,139(85.5%) kfrequencies in the basic level and 691(8.1%) frequencies in the further level. However total elements appeared 529(6.4%) frequencies in the supplementary level. The kinds and frequencies of the elements for the inquiry context suggested in the basic level were more than those in the supplementary and in the further level. The social context was not appeared in the supplementary level. However five inquiry context elements were all appeared in the basic and further level.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.3
• /
• pp.304-309
• /
• 2007

What is important in ubiquitous computing is collecting users' context information from various sensors and providing services suitable for use's current situation. Particularly in mobile environment, each area has different context awareness structure and this makes it difficult to share information with other areas. As a result, context resources for recognizing users' context ate insufficient. Moreover, because mobile devices have a limited processing capacity, there are difficulties in the real time analysis of users' context. This paper proposed a context awareness and integration model for analyzing users' context actively and providing adaptive services using mobile devices. The proposed model distinguishes users' context between dynamic and static structure to analyze the context, and obtains context resources by sharing context information of users within an area.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.1 s.39
• /
• pp.185-194
• /
• 2006

The ubiquitous computing environment focuses on recognizing the context and Physical entities, whereas, previous computing environments mainly focused on the conversational interactions between the computer and the user. For this reason, there has been an increase in the research of context aware computing environments. In previous researches , context services are designed using context ontology used in context aware middleware. So, context service cannot change the context ontology in execution time. We propose a hierarchical context ontology management for context aware service to change their ontology in execution time. And we also a resolution model for context conflict which is occurred in inference of context. We have designed a middleware based on this model and implemented the middleware. As the middleware is implemented on the OSGi framework, it can cause interoperability among devices such as computers, PDAs, home appliances and sensors. It can also support the development and operation of context aware services, which are required in the ubiquitous computing environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.285-288
• /
• 2004

스마트 홈은 유비쿼터스 환경의 각종 센서와 정보가전에서 얻어지는 데이터에서 사용자의 Context를 추출하여 사용자에게 적응적인 서비스를 제공한다 지금까지의 Context는 사용자가 한 명일 경우를 가정하였지만 실제 집이라는 공간은 가족이라는 구성원이 함께 생활하는 공간으로 동시에 여러 개의 Context가 존재하며 이러한 Context는 서로 충돌할 수도 있다. 본 논문에서는 집에서 여러 Context들 간에 충돌이 일어났을 때 이를 해결하는 방법을 제안한다. 집은 여러 사용자가 공유하고 있지만 각 구성원의 침실이나 화장실처럼 한 개인의 영역이 존재한다 또한 침실은 쉬는 곳, 주방은 요리를 하고 음식을 먹는 곳, 거실은 가족끼리의 모임을 갖거나 TV 시청, 음악감상 등의 여가를 즐기는 곳 등 공간마다 나름의 용도를 가지고 있다 본 논문은 Context들간의 충돌을 조정을 위해 이러한 공간의 특성을 이용할 것을 제안한다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.3
• /
• pp.165-170
• /
• 2007

Recommendation systems provide users with proper services using context information being input from many sensors occasionally under ubiquitous computing environment. But in case there isn't sufficient context information for service recommendation in spite of much context information, there can be problems of resulting in inexact result. In addition, in the quantification step to use context information, there are problems of classifying context information inexactly because of using an absolute classification course. In this paper, we solved the problem of lack of necessary context information for service recommendation by using dynamic profile information. We also improved the problem of absolute classification by using a relative classification of context information in quantification step. As the result of experiments, expectation preference degree was improved by 7.5% as compared with collaborative filtering methods using an absolute quantification method where context information of P2P mobile agent is used.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.3
• /
• pp.239-248
• /
• 2006

Current context-aware applications In ubiquitous computing environments make the assumption that the context they are dealing with is correct. However, in reality, both sensed and interpreted context informations are often uncertain or imperfect. In this paper, we propose a probability extension model to ontology-based model for rep resenting uncertain contexts and use Bayesian networks to resolve about uncertainty of context informations. The proposed model can support the development and operation of various context-aware services, which are required in the ubiquitous computing environment.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.4
• /
• pp.423-429
• /
• 2006

The systems in the ubiquitous computing environment need to provide users with context-aware services, intelligently interacting with the surrounding environment. Therefore, the systems in the ubiquitous computing environment require context-awareness ability in order to gather and analyze context information in various situations and environments. However, existing context-aware systems lack the ability to systematically generate and handle various types of context information, and only a few systems have ability learning from environment. In this paper, a general context model is defined to describe various contexts and a context-awareness framework is implemented based in the model, which makes it straightforward to handle and generate various types of context from diverse sensor. The framework is designed to allow a system to sensed, combined, inferred, and learned context information, in order to provide users with services in dynamic environments. We have implemented the proposed framework and applied it to a u-Health management system.