• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1843-1854
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• 2010

The utilization of underground space has recently increased with the complication of road, the rise of the land price, and the development of green technology. Underground space ranges from classical excavations to subway, underground cities, and shopping malls where there are crowds of people. At this time, government has spent a lot of money in installing various types of safety facilities for preparations of increasing potential disasters. Therefore, an effective facility management system is required. In this paper, we propose an information retrieval process to effectively extract the facilities' information based on the ontology and spatial analysis in underground space. The ontology-based searching supports hierarchical and associated results as well as knowledge sharing with hierarchy concepts. The spatial analysis based searching has "Buffer" and "Near" functions to operate on a map without understanding any property of the facility information.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.523-530
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• 2014

Ontology alignment is the way to share and reuse of ontology knowledge. Because of the ambiguity of concept, most ontology alignment systems combine a set of various measures and complete enumeration to provide the satisfactory result. However, calculating process becomes more complex and required time increases exponentially since the number of concept increases, more errors can appear at the same time. Lately the focus is on meta-matching using the heuristic algorithm. Existing meta-matching system tune extra parameter and it causes complex calculating, as a consequence, the results in the various data of specific domain are not good performed. In this paper, we propose a high performance algorithm by using DCS that can solve ontology alignment through simple process. It provides an efficient search strategy according to distribution of Levy Flight. In order to evaluate the approach, benchmark data from the OAEI 2012 is employed. Through the comparison of the quality of the alignments which uses DCS with state of the art ontology matching systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.173-182
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• 2001

In this paper, we discuss how ontology Plays roles in building a distributed and heterogeneous knowledge-base system. First, we discuss relationship between ontology and agent in the Knowledgeable Community which is a framework of knowledge sharing and reuse based on a multi-agent architecture. Ontology is a minimum requirement for each agent to join the Knowledgeable Community. Second we explain mediation by ontology to show how ontology is used in the Knowledgeable Community. A special agent called mediation analyzes undirected messages and infer candidates of recipient agents by consulting ontology and relationship between ontology and agents. Third we model ontology as combination of aspects each of which can represent a way of conceptualization. Aspects are combined either as combination aspect which means integration of aspects or category aspect which means choice of aspects. Since ontology by aspect allows heterogeneous and multiple descriptions for phenomenon in the world, it is appropriate for heterogeneous knowledge-base systems. We also show translation of messages as a wave of interpreting multiple aspects. A translation agent can translate a message with some aspect to one with another aspect by analyzing dependency of aspects. Mediation and translation of messages are important to build agents easily and naturally because less knowledge on other agents is requested for each agent.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.365-374
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• 2005

The B2B electronic product commerce needs intermediary system to provide an integrated interface for the parts libraries of multiple suppliers. However, it is difficult to automatically integrate the parts libraries because they are heterogeneous. Existing ontology-based approaches show a limited functionality of automated integration of information because Dey can not prevent ontologies from being modeled in different ways, so that the inter-ontology mappings to resolve the heterogeneity become complicated and arbitrary. In order to overcome such problems this paper proposes an ontology modeling framework for parts libraries based on the Guarino's theory of upper ontology. The framework provides knowledge modeling primitives which have explicit formal meanings and modeling principles based on ontological natures. Using the framework, ontology developers can model the knowledge of parts libraries systematically and consistently, so that the resulting ontologies become comparable and uniform and the ontology merging algorithm for the automated information integration can be easily developed.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.5
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• pp.942-949
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• 2009

We in this paper propose the method for diagnosis patients through the reasoning based on the diagnosis ontology in oriental medicine. In prior studies, it is simply diagnosed with the information of main symptoms, optional symptoms, and tongue / pulse. In addition, ontology itself has subjective opinions of oriental medical doctors for patients in form of axioms. There is a problem in latter case that it is difficult for other oriental medical doctors to change knowledge within the ontology. In order to solve these problems, we have constructed the diagnosis ontology and the reasoning algorithm as followings: First, in order to raise the diagnosis accuracy, we constructed the diagnosis ontology with pattern identifications, main symptoms, optional symptoms, and tongue / pulse. We also utilize the diagnosis points described in the pathology textbook, which has been studied in all of domestic oriental medical colleges. This information is represented as OWL instances in ontology, not OWL axioms so that it can be easily updated. Second, we suggest the algorithms for diagnosis reasoning and learning method based on the ontology. We have implemented the reasoning and learning system according to the diagnosis algorithm. In future study, we will construct the diagnosis ontology with all of pattern identifications and symptoms within the pathology textbook.

• Journal of Korean Library and Information Science Society
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• v.43 no.3
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• pp.143-163
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• 2012

In order to convert a thesaurus described by a person to ontology, the first step is to translate the thesaurus to the ontology by using SKOS, which is suitable for conversion to ontology and was chose an international standard by W3C. SKOS is suitable for converting thesaurus or subject headings or classification system to ontology, but we need a web language to describe an ontology as RDF/XML. RDF/XML is so difficult to read and write that we can need RDFa embedded in HTML document or Turtle, which is more easily describable and readable. Along with description using SKOS, this research has experimentally constructed the ontology by using ontology construction program $Prot{\acute{e}}g{\acute{e}}$ 4.2. In addition to basic concept relationships of thesaurus like equivalent relationship, hierarchical relationships, association relationships transitive hierarchical relationships are included suggested by SKOS in this research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2777-2784
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• 2012

To support complex business environment. the enterprise information system requires prompt and flexible response to altered conditions. The development of collaboration among information systems in accordance with changes in enterprises' business environment brings about the problems of duplication of the existing business services and increase in costs of maintenance. In order to supplement and resolve such problems, researches on ontology are under way. Ontology can support the semantic interoperability of Web service by describing the resources of particular business domains and the relationships among them. This thesis suggests ontology that supports interoperability among services. The constructed ontology is designed into the service area, the meta area, and the instance area, which can support the collaboration efficiently by providing the link between the interactivity among businesses and the data. The register and call of constructed ontology are carried out with the interaction of the three areas, that is, the service area, the instance area and the meta area that supports the common elements. The efficiency of the proposed ontology is evaluated by comparing with an existing Web service ontology.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.2
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• pp.7-11
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• 2012

In this paper, we defined constructivism and ontology theory and associate it in ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.99-108
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• 2007

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.