• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.814-820
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• 2008

Recently, researches on ontology-based pattern classification have been tried out in many fields. However, in most of the researches, the ontology which represents the knowledge about pattern classification is just referred during the processes of the pattern classification. In this paper, we propose ontology-based fuzzy classifier for pattern classification which is extended from the fuzzy rule-based classifier In order to realize the proposed classifier, we construct an ontology by conceptualizing the method of fuzzy rule-based pattern classification and generate ontology inference rules for pattern classification. Lastly, we show the validity o) the proposed classifier through the experiment of pattern classification on the Fisher's IRIS dataset.

• ETRI Journal
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• v.42 no.2
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• pp.247-257
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• 2020

Spatial experiences in route finding, such as the ability of finding low-traffic routes, exert a significant influence on travel time in big cities; therefore, the spatial experiences of seasoned individuals such as taxi drivers in route finding can be useful for improving route-finding algorithms and preventing using routes having considerable traffic. In this regard, a spatial experience-based route-finding algorithm is introduced through ontology in this paper. To this end, different methods of modeling experiences are investigated. Then, a modeling method is chosen for modeling the experiences of drivers for route finding depending on the advantages of ontology, and an ontology based on the taxi drivers' experiences is proposed. This ontology is employed to create an ontology-based route-finding algorithm. The results are compared with those of Google maps in terms of route length and travel time at peak traffic time. According to the results, although the route lengths of route-finding method based on the ontology of drivers' experiences in three cases (from nine cases) are greater than that based on Google maps, the travel times are shorter in most cases, and in some routes, the difference in travel time reaches only 10 minutes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.591-593
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• 2010

The Ontology is the concept of human beings in any sense to classify things as departure from the classification based on the meaning at the prensent situation and concepts as the object of the Ontology. also, the technology is shared the conceptualization in a formal ontology as a meaning to give a clear description to the conceptual engineering in the ontology. Specialized multimedia broadcasting of TV-Anytime standard and multimedia representation of the overall standard of the MPEG-7 based on the concept of broadcasting multimedia presentations that can be used to develop an ontology who is required. In this paper, in TV-Anytime and MPEG-7 multimedia standard for broadcasting multimedia contents based on standards developed for the ontology, an ontology language for expressing OWL (Web Ontology Language) and RDF (Resource Description Framework) and the broadcast contents using To represent metadata of the system who has been developed.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.202-208
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• 2006

The goal of this study is to develop knowledge representation method for the construction and evaluation of ontology for diagnosis in oriental medicine. To develop the expert system for decision making on diagnosis and treatment, the systematic and structural knowledge which can be processible in EMR(Electronic Medical Record) must be precedent, and the Computational Process which control the system as well. This study set up an ontology as a trial model to represent the oriental medical knowledge into the machine processible one. Protege 2.1 has been used to build the ontology, and the serialization format of our ontology is the XML document based on OWL. The components of oriental medical diagnosis was arranged with the combination of symptoms which belong to the certain symptom patterns. Then natural language which expresses the oriental medical diagnosis components were converted into the logical sentence, and individual characteristic symptoms into each values of specific properties. In addition to the study, the diagnosis software for oriental medicine was developed and it used the ontology which we developed. Sequently, we tested the software to confirm the appropriateness of ontology. The result of the test shows that diagnostic questions are automatically formulated according to the diagnosis components of this ontology and that as such diagnostic results are induced. Therefore, the ontology system in this study will be efficient to develop the diagnosis program and useful as a tool for doctors to make decision. But, it is not recommendable to apply the system to the clinical environment until the clear diagnosis standards are introduced, and the more reliable diagnosis program can be developed based on the more appropriate ontology mentioned above.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.411-417
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• 2020

To utilize building information modeling (BIM) technology at the bridge maintenance stage, it is necessary to integrate large quantities of bridge inspection and model data for object-oriented information management. This research aims to establish the benefits of utilizing the extended industry foundation class (IFC)-BIM and ontology for bridge inspection information management. The IFC entities were extended to represent the bridge objects, and a method of generating the extended IFC-based information model was proposed. The bridge inspection ontology was also developed by extraction and classification of inspection concepts from the AASHTO standard. The classified concepts and their relationships were mapped to the ontology based on the semantic triples approach. Finally, the extended IFC-based BIM model was integrated with the ontology for bridge inspection data management. The effectiveness of the proposed framework for bridge inspection information management by integration of the extended IFC-BIM and ontology was tested and verified by extracting bridge inspection data via the SPARQL query.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

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.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.26-31
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• 2004

In the last few years, The Semantic Web has increased the interest in ontologies. Ontology is an essential component of the semantic web. Ontologies continue to change and evolve. We consider the management of versions in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. In many cases, we want to be able to search in historical versions, query changes in versions, retrieve versions on the temporal dimension. In order to support an ontology query language that supports temporal operations, we consider temporal dimension includes transaction time and valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the storage policies that are storing all the versions, all the sequence of changed element, all the change sets, the aggregation of change sets periodically, and the aggregation of change sets using a criterion. We conduct a set of experiments to compare the performance of each storage policies. We present the experimental results for evaluating the performance of different storage policies from scheme 1 to scheme 5.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.766-771
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• 2006

In this paper, we focus on the building domain ontology from corpus by extracting concepts and properties relationships based on linguistic patterns. The pharmacy field is selected as an experiment domain and we present an algorithm to extract hierarchical structure for terminology based on the noun/suffix patterns of terminology in domain texts. In order to show usefulness of our domain ontology, we compare a typical keyword based retrieval method with an ontology based retrieval mettled which uses related information in an ontology for a related feedback. As a result, our method shows the improvement of precision by 4.97% without losing recall.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.321-330
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• 2023

In this paper, we propose a method of automatically creating an ontology by extracting various relationships between terms necessary for constructing an ontology of a specific domain. The extracted relationship is constructed as an ontology by encoding it into an axiomatic set in the structure of the ontology. To solve efficiently, we represent the search space of the set as an integer programming problem, and we reduce the matrix by using a simple reduction that eliminates rules that are not very helpful for optimization. In conclusion, this paper proposes a way to generalize patterns using given data, reduce search space while maintaining useful patterns, and automatically generate efficient ontology using extracted relationships by applying algorithms composed of structured ontology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.183-190
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• 2012

This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.