• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.337-338
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• 2006

The requirement to reuse a design knowledge have been enlarged with the automation of a design system. A design knowledge gives logical and technical meanings to design data of a problem area. The representation of the knowledge is distributed and developed independently. For this reason, we need a general methodology with a semantic interoperability of design knowledge. In this paper, we accept previous requirements by using semantic query system with ontology repository.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.242-248
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• 2014

With the rapidly growing amount of information represented in RDF format, efficient querying of RDF graph has become a fundamental challenge. SPARQL is one of the most widely used query languages for retrieving information from RDF dataset. SPARQL is not only simple in its syntax but also powerful in representation of graph pattern queries. However, users need to make a lot of efforts to understand the ontology schema of a dataset in order to compose a relevant SPARQL query. In this paper, we propose a graph query formulation and processing scheme based on ontology schema information which can be obtained by summarizing RDF graph. In the context of the proposed querying scheme, a user can interactively formulate the graph queries on the graphic user interface without making efforts to understand the ontology schema and even without learning SPARQL syntax. The graph query formulated by a user is transformed into a set of class paths, which are stored in a relational database and used as the constraint for search space reduction when the relational database executes the graph search operation. By executing the LUBM query 2, 8, and 9 over LUBM (10,0), it is shown that the proposed querying scheme returns the complete result set.

• Korean Journal of Oriental Medicine
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• v.12 no.2 s.17
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• pp.31-45
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• 2006

Bioinformatics and medical informatics have moved to make its knowledge more systematically and computationally using ontology. These ontologies help querying ring and analyzing data and used to develop application in biomedical. However, no research about ontology of oriental medical exists. Thus, to maximize the power of transitional knowledge, it is necessary to construct the ontology for oriental medical. This paper compares the ontologies of bio and medic by an objective point of view to guide the construction of oriental medic ontologies.

• Genomics & Informatics
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• v.13 no.1
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• pp.7-14
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• 2015

During recent years, there has been exponential growth in biological information. With the emergence of large datasets in biology, life scientists are encountering bottlenecks in handling the biological data. This study presents an integrated geographic information system (GIS)-ontology application for handling microbial genome data. The application uses a linear referencing technique as one of the GIS functionalities to represent genes as linear events on the genome layer, where users can define/change the attributes of genes in an event table and interactively see the gene events on a genome layer. Our application adopted ontology to portray and store genomic data in a semantic framework, which facilitates data-sharing among biology domains, applications, and experts. The application was developed in two steps. In the first step, the genome annotated data were prepared and stored in a MySQL database. The second step involved the connection of the database to both ArcGIS and $Prot{\acute{e}}g{\acute{e}}$ as the GIS engine and ontology platform, respectively. We have designed this application specifically to manage the genome-annotated data of rumen microbial populations. Such a GIS-ontology application offers powerful capabilities for visualizing, managing, reusing, sharing, and querying genome-related data.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.35-44
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• 2011

Ontologies are playing an important role in semantic web which is emerging as a next stage of the web revolution because various kinds of metadata are described in ontologies. Correspondingly, many query languages like SPARQL, RDQL etc. have been proposed for querying these ontologies. But users have to know the structures and resource names of ontologies completely to get search results even if they have expertise on complex formal logic and syntax of the query languages. Especially, casual users do not know the resource names and may use different words from resource names when they write their query language. This vocabulary gap problem have to be solved to raise the success rate. In this paper, an approach for translating user's search words to corresponding resource names has been proposed. This approach uses semantic similarity between user created search words and ontology resource names.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.219-228
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• 2006

Many biomedical research groups have been trying to share their outputs to increase the efficiency of research. As part of their efforts, a common ontology named Gene Ontology(GO), which comprises controlled vocabulary for the functions of genes, was built. However, data from many research groups are distributed and most systems don't support integrated semantic queries on them. Furthermore, the semantics of the associations between concepts from external classification systems and GO are still not clarified, which makes integrated semantic query infeasible. In this paper we present an ontology matching and integration system, called AutoGOA, which first resolves the semantics of the associations between concepts semi-automatically, and then constructs integrated ontology containing concepts from GO and external classification systems. Also we describe a web-based application, named GOGuide II, which allows the user to browse, query and visualize integrated data.

• Korean Journal of Computational Design and Engineering
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• v.20 no.2
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• pp.159-170
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• 2015

Radio-Frequency Identification (RFID) or Near Field Communication (NFC) technology has many advantages over other visual interfaces since it does not require line-of-sight alignment, can identify multiple tags simultaneously, and does not destroy the integrity of original objects. In addition, smart devices such as smartphone and smartpad have NFC/RFID readers which can provide mobile and natural interactions with digital and physical contents. Augmented reality has an excellent visual interaction capability with digital contents in a real environment by embedding digital contents into the physical world. In this paper, we propose a new approach to digital content interactions using RFID/NFC-based tangible interfaces in augmented reality environments that utilize invisible interfaces in addition to marker-based visual interfaces. By combining the advantages of invisible and visual interfaces, more intuitive interactions with digital contents can be provided, which can remove the difficulty of using typical AR paddles that are widely used in AR interactions. In particular, a semantic AR ontology is defined to provide more convenient interactions. Through the semantic ontology-based inferencing, physical querying and filtering are effectively supported. We will show the effectiveness and advantage of the proposed approach by demonstrating implementation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.422-430
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• 2008

Data integration is techniques to combine heterogeneous data from different sources, and to allow users to transparently access all data from multiple sources via a single view. The difficulty with data integration is data heterogeneity (i.e. schema heterogeneity, semantic heterogeneity). Richer semantics of data is a major factor in resolving conflicts among heterogeneous data sources. As UML class model represents only schema-based semantics of data, alternative methods such as ontology is useful for representing additional semantics. This paper proposes a method for integrating two data sources with UML class models by using an analysis of their ontologies. In our framework, ontology will be applied to describe semantics of data in each source. Then the ontologies are analysed and compared to determine their similarities and differences. The result of the comparison is used to devise an integrated ontology that will enable querying on the integrated information.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.206-216
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• 2007

With respect to the Semantic Web proposed to overcome the limitation of the Web, OWL has been recommended as the ontology language used to give a well-defined meaning to diverse data. OWL is the representative ontology language suggested by W3C. An efficient retrieval of OWL data requires a well-constructed storage schema. In this paper, we propose a storage schema construction technique which supports more efficient query processing. A retrieval technique corresponding to the proposed storage schema is also introduced. OWL data includes inheritance information of classes and properties. When OWL data is extracted, hierarchy information should be considered. For this reason, an additional XML document is created to preserve hierarchy information and stored in an XML database system. An existing numbering scheme is utilized to extract ancestor/descendent relationships, and order information of nodes is added as attribute values of elements in an XML document. Thus, it is possible to retrieve subclasses and subproperties fast and easily. The improved query performance from experiments shows the effectiveness of the proposed storage schema construction and retrieval method.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.31-41
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• 2009

In the Semantic Web, it is possible to provide intelligent information retrieval and automated web services by defining a concept of information resource and representing a semantic relation between resources with meta data and ontology. It is very important to manage semantic data such as ontology and meta data efficiently for implementing essential functions of the Semantic Web. Thus we propose an index structure to support more accurate search results and efficient query processing by considering semantic and structural features of the semantic data. Especially we use a graph data model to express semantic and structural features of the semantic data and process various type of queries by using graph model based path expressions. In this paper the proposed index aims to distinguish our approach from earlier studies and involve the concept of the Semantic Web in its entirety by querying on primarily extracted structural path information and secondary extracted one through semantic inferences with ontology. In the experiments, we show that our approach is more accurate and efficient than the previous approaches and can be applicable to various applications in the Semantic Web.