• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.27-44
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• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.200-207
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• 2009

U-Healthcare is more efficient as a solving method for health problems rather than visiting the hospital. Recently, systems have been studied to offer appropriate service to user, which gather and analyze biological signals of a user and context information around the user from a variety of sensors. The existing systems for U-Healthcare are based on domain specific service so it is difficult to expand and link to other systems. Also, they lack services focusing on the specific quality of the user, because they offer a general service which targets a lot of users. To address this problem, we expand an extensibility of system using the context-awareness agent based on multi-agents. Also, we provide the suitable services which match with the context information of user to each user using the modeling toolkit JaUCE based on GUI. We design and implement U-Silvercare service to demonstrate the effectiveness of the proposed context-awareness agent and modeling toolkit.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.185-193
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• 2010

With the emergence of ubiquitous computing era, various models for providing personalized service have been proposed, and, especially, several recommendation service schemes have been proposed to give tailored services to users proactively. However, the previous recommendation service schemes utilize a wide range of data without and filtering and consider the limited context-aware information to predict user preferences so that they are not adequate to provide personalized service to users. In this paper, we propose an adaptive recommendation service scheme which proactively provides suitable services based on the current context. We use accumulated interaction contexts (IC) between users and devices for predicting the user's preferences and recommend adaptive service based on the current context by utilizing clustering and collaborative filtering. The clustering algorithm improves efficiency of the recommendation service by focusing and analyzing the data that is collected from the locations nearby the users. Collaborative filtering guarantees an accurate recommendation, even when the data is insufficient. Finally, we evaluate the performance and the reliability of the proposed scheme by simulations.

• The Journal of Society for e-Business Studies
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• v.12 no.2
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• pp.1-16
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• 2007

Recently the computing environment has been moved to open architectures that include Web technologies. Web Service is one of import component of the new paradigm. This paper presents a design and implementation of GIS Web Service for mobile devices. As many mobile devices are equipped with GPS (Global Positioning System), it is required to handle the position information more effectively. We have extended the proxy program in the client device to actively send the context information to the server. Based on the context information the server determines the optimal service mode to a particular client. A working example of location?based GIS Web Service is also presented. By using Web Service standards and XML messages we can achieve the maximal interoperability for heterogeneous mobile devices.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.452-456
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• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.429-436
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• 2013

Context aware environment u-health service is to provide health service with recognition of a computer. The computer recognizes that a patient can contact real life in many context. Context aware environment service for recommend have to definition of context data and service recommendations related to factors shall be identified. In this paper, Context aware environment of u-health service will be provide context data related to identifies recommendations factors using multivariate analysis method and recommendations factors creation to decision tree, association rule based decision model. health service recommend for significantly context data can be distinguish through recommendation factors of identify. Also, context data of patient can know preference factors through preference decision model.

• KSCI Review
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• v.14 no.1
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• pp.165-173
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• 2006

To support service based on context-aware in ubiquitous computing environment, there are required context managing, context reasoning and context modeling technologies. In this paper, we propose a hierarchical ontology-based context management model and design a context-aware middleware based on this model for supporting active application adaptability and reflecting users' requirements dynamically in contextual changes. It also provides efficient support for inferencing, interpreting, acquiring and discovering various contexts to build context-aware services and presents a resolution method for context conflict which is occurred in execution of service. The proposed middleware can support the development and operation of various context-aware services, which are required in the ubiquitous computing environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.119-126
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• 2009

In recent years, many recommendation service systems that search or recommend information automatically considering user's taste or property are developed. However, there is a weak point that correct recommendation is hard without considering the preference of user's context. This paper proposes a filtering method that gives correct recommendation considering the preference of user's context. To support this method, we get UCOP(User-Context Object Preference) using the preference of user's context and Pearson correlation coefficient. The results of the experiment show the improvement of 11%, 2% of precision and 8%, 4% of recall comparing with the existing service systems. Our recommendation service systems show 77% of precision and 53% of recall overall.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.101-106
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• 2014

Information and Communication Technology environment has been developing rapidly and variety of services are in service. As data becomes increasingly sophisticated. These data was applied techniques of visualization in order to visualize efficiently. Various agencies are providing the map based data in real-time. However, traffic information is getting more complex and users are having a difficulty to understand with convential visualization techniques. This study was designed and implemented in the web service of traffic information using Focus+Context. Web service implemented HTML5(Hyper Text Markup Language 5), and it runs on browser of either desktop or mobile devices. This study sets an example as web application from a user perspective by combining information visualization and traffic information.