• Journal of Information Technology Services
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• v.12 no.1
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• pp.323-340
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• 2013

As the importance of collaboration becomes critical in today's open and complex business environment network, the issues and solutions on compatibility and reusability between different kinds of applications are being increasingly important as well in systems analysis and design. And therefore, service-centered SOA is receiving attention in such business environment as a strategic approach that makes possible for prompt action according to the needs of users and business process. Various implementation methodologies have been proposed for SOA, however, in practical aspects most of them have some problems since they fail to propose specific policies in definition and identification of services for the exact user requirements and business situations. To solve or alleviate those problems, this paper suggests a new service identification model based on hierarchical ontology, where three different ontologies such as business ontology, context ontology and service ontology are proposed to define the relationship and design the link between user requirements, business process, applications and services. Through a suggested methodology in this paper, it would be possible to provide proactive services that meets a variety of business environments and demands of user. Also, since the information can be modified adaptively and dynamically by hierarchical ontology, this study is expected to play a positive role in increasing the flexibility of systems and business environments.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.11-18
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• 2009

As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.333-342
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• 2010

Building ontology is the key factor to construct semantic web. However, this is time-consuming process. Hence, there are several approaches which automatically generate the ontologies from relational databases. Current studies on the automatic generation of the ontologies from relational database are focused on generating the ontology by analyzing the database schema and stored data. These studies generate the ontology by analyzing only tables and constraints in the schema and ignore view definitions. However, view definitions are defined by a database designer considering the domain of the database. Hence, by considering view definitions, additional classes and hierarchical relationships can be generated. And these are useful in answering queries and integration of ontologies. In this paper, we formalize the generation of classes and hierarchical relationships by analyzing existing methods, and we propose the method which generates additional classes and hierarchical relationships by analyzing view definitions. Finally, we analyze the generated ontology by applying our method to synthetic data and real-world data. We show that our method generates meaningful classes and hierarchical relationships using view definitions.

• 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 KIISE:Software and Applications
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• v.31 no.3
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• pp.353-360
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• 2004

Ontology defines the terms used in a specific domain and the relationships between them and represents them as hierarchical taxonomy. The present paper proposes a semi-automatic domain-specific ontology construction method based on terminology Processing. For this purpose, it presents an algorithm to extract terminology according to the noun/suffix pattern of terminology in domain texts and find their hierarchical structure. The experiment was carried out using pharmacy-related documents. As singleton terminology with noun/suffix were identified, the average accuracy was 92.57%. In case of multi-word terminology, the average accuracy was 66.64%. The constructed ontology forms natural semantic clusters with based on suffices and semantic information, so can be utilized in approaches to specific knowledge such as information look-up or as the base of inference to improve searching abilities.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.31-47
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• 2008

As OWL(Web Ontology Language) has been selected as a standard ontology description language by W3C, many ontologies have been building and developing in OWL. The lena developed by HP as an Application Programming Interface(API) provides various APIs to develop inference engines as well as storages, and it is widely used for system development. However, the storage model of Jena2 stores most owl documents not acceptable into a single table and it shows low processing performance for a large ontology data set. Most of all, Jena2 storage model does not consider hierarchical structures of classes and properties. In addition, it shows low query processing performance using the hierarchical structure because of many join operations. To solve these issues, this paper proposes an OWL ontology relational database model. The proposed model semantically classifies and stores information such as classes, properties, and instances. It improves the query processing performance by managing hierarchical information in a separate table. This paper also describes the implementation and evaluation results. This paper also shows the experiment and evaluation result and the comparative analysis on both results. The experiment and evaluation show our proposal provides a prominent performance as against Jena2.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.69-74
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• 2009

In this paper, we propose a method of ontology-based control of autonomous robots. Advancing one step further from using ontology as a hierarchical storage of information, the proposed method shows how to control robots through ontology inference. That is, the information on obstacles detected by robots is represented as an ontology, and robots' action planning and control are performed according to robots' surroundings through ontology inference. We make a differentially driven robot and illustrate the effectiveness of the proposed method via the experiment of the robot's navigation in real environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.182-187
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• 2006

This paper proposes a method for boundary recognition of named entity using hidden markov model and ontology information of biological named entity. We uses smoothing method using 31 feature information of word and hierarchical information to alleviate sparse data problem in HMM. The GENIA corpus version 2.1 was used to train and to experiment the proposed boundary recognition system. The experimental results show that the proposed system outperform the previous system which did not use ontology information of hierarchical information and smoothing technique. Also the system shows improvement of execution time of boundary recognition.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.47-56
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• 1998

This is a study on an ontology development for a content-based Expert System Document Categorization. The objectives of this study were to set up the concept of ontology and to find out the effect of ontology on Expert System. Based on this concept of ontology, it found noems for development of Expert System in the field of fine arts and showed Ontology hierarchical categorization.