• International journal of advanced smart convergence
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• v.6 no.3
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• pp.17-21
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• 2017

In this paper, the service execution accuracy was compared by ontology based rule inference method and machine learning method, and the amount of data at the point when the service execution accuracy of the machine learning method becomes equal to the service execution accuracy of the rule inference was found. The rule inference, which measures service execution accuracy and service execution accuracy using accumulated data and pattern matching on service results. And then machine learning method measures service execution accuracy using cross validation data. After creating a confusion matrix and measuring the accuracy of each service execution, the inference algorithm can be selected from the results.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.145-170
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• 2003

Open Decision Support System(DSS) is an automated and transparent system that is built to be shared both within and across organizations. The open DSS has been thought to be a set of decision components that are communicating through Web protocols. These characteristics intuitively invite the Web services concepts, which are currently one of the new trends in network-based business services. However, web services still are not active enough to be autonomous, and to provide for composing functionalities. These lead to the motivation on building a sophisticated web service to contain these features and to utilize web services on behalf of the user. This paper aims to propose a new concept of Meta Web Service, a web service-based open DSS. Decision modules in a dynamic and open DSS can be viewed as a web service. The Meta Web Service understands the users problem statement with ontology, performs web service discovery, web service composition, and automatically generates codes for composite web service execution. A prototype of example web service has been developed to show the feasibility of the proposed idea.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

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.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.192-201
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• 2005

For the past ten years, the goal of ubiquitous computing research has been the establishment of a new technology system with the aim 'Anytime, Anywhere, and Any form'. The needs for agent technology innovations such as ontology-based structure, ontology-based agent communication language, and multi-agents frameworks have been identified. This paper proposes a noble multi-agents architecture for ubiquitous systems. We suggest four major steps in the interaction between human and agents which enable ubiquitous agents to process by themselves to provide adaptive service to meet human's needs. First, we propose a semantic web technology to represent the association between information resources more explicitly Second, we construct a semantic ontology so that agents can recognize web contents.'Third, we propose a method to communicate between agents using OWL ontologies. Finally, we suggest a multi-agents structure based on the JADE of FIPA to analyze messages and get information. The semantic multi-agents framework proposed in this paper infers semantic situations using semantic web technology based on ontologies. A service provided is inferred differently according to user state because the multi-agents communicate by using OWL ontology language. Therefore, our system better infers context information than other without ontologies.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.309-315
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• 2012

The dissemination of smartphones is being spread and supplementary services using smartphones are increasing and various as the Mobile network and device are developing rapidly, so smartphones that enables to provide a wide range of services is expected to receive the most attention. It makes users listen to music anytime, anywhere in real-time, use useful applications, and access to Internet to search for information. The service environment is changing on PC into Mobile due to the change of the circumstance mentioned above. these services are done by using just location information rather than other context, and users have to search services and use them. It is essential to have Context-aware technology for personalization recommendation services and the appropriate representation and definition of Context information for context-aware. Ontology is possible to represent knowledge freely and knowledge can be extended by inferring. In addition, design of the ontology model is needed according to the purposes of utilization. This paper used context-aware technologies to implement a user personalization recommendation service. It also defined the context through OWL modeling for user personalization recommendation service and used inference rules and inference engine for context reasoning.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.37-45
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• 2013

In this paper proposes the latest network-assisted online telemedicine service to coincide with the point being discussed for health care providers to match patients, patients with personalized medical service support system. In order to design the system, to understand the requirements of the patient personalized medical support service system, the data were normalized and were designed architecture client server structure. Further, in order to implement the system that was designed to define the structure of server and client, ontology repository, we implement the system. In this paper, as a result of the test by creating a scenario and prerequisites for testing patient personalized medical service support system that is design and implementation, selecting a patient's condition, department of symptoms by the selected but it was confirmed that the inference is, inference medical institutions that fits department inferred one following upon the items medical patient has the required.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.453-459
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• 2009

In recently, as the interest of media contents increase among internet users, a variety of media contents are circulated in the web. Especially, video-media content in media contents attracts internet user's interest. In conjunction with web 2.0, internet users open and share their making contents by themselves. Their attitude about accepting media contents is not passive but aggressive. Additionally, they create new form of distribution of the flow. Video media content for distribution on the Web is created by experts to a professional content, but Web 2.0 era, the UCC (User Create Contents) in the form of self-produced content is the most. The generated media by the general internet users, but self-produced content, provides video information only and has limitations. To satisfy internet users as consumers in the web 2.0 eras, it has needed to provide actual feeling contents that add various effects not just simple media. Therefore, this paper represents the existing media content with simple information based on the concept of ontology and the meaning to the subject for the media content. We will provide an actual feeling how to offer the configuration of a service model (AF-VS : Actual Feeling Video Service).

• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• Journal of Service Research and Studies
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• v.4 no.1
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• pp.49-59
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• 2014

Context-aware computing is an emerging paradigm to achieve ubiquitous computing environments by enabling computer systems to understand their situational contexts. A context-aware system uses context to provide relevant information and services to the user depending on the user's task. In this paper, we propose an ontology-based context-aware modeling methodology that transmits low-level contexts acquired by directly accessing various sensors in the physical environments to high-level contexts. With these high-level contexts, context-aware application can provides proactive and intelligent services using ECA (Event-Condition-Action) rules. We implemented a home robot service in smart office environment.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.109-111
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• 2004

대표적인 시맨틱 웹 서비스 발견 기술은 OWL-S와 MIT의 Process Handbook이 있다. 그러나. OWL-S는 개발 초기 단계이기 때문에, 아직 효과적인 웹 서비스 발견을 제공하기에는 몇 가지 제약 조건을 가지고 있다. 예를 들어. 정보 전송을 위한 제악 조건과 실행에 따른 상태 변환 정보를 정의하고 있지 않다. 또한. 사용자가 원하는 프로세스들의 시맨틱 정보들을 정의하고 있지 않다. 반면, MIT Process Handbook은 OWL-S와 같이 서비스 모델에 대한 상세한 정보들을 정의하고 있지 않아, 서비스 작성에 필요한 서비스들을 찾기가 어렵다. 그러므로, 본 논문에서는 Topic Maps 기반의 TM-S(Topic Maps for Service)를 제안하였다.