• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.50-52
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• 2009

Ontology maintenance is a time consuming and costly process which requires special skill and knowledge. It requires joint effort of both ontology engineer and domain specialist to properly maintain ontology and update knowledge in it. This is specially true for medical domain which is highly specialized domain. This paper proposes a novel approach for maintenance and update of existing ontologies in a medical domain. The proposed approach is based on modified Ontology Maturing Process which was originally developed for web domain. The proposed approach provides way to populate medical ontology with new knowledge obtained from medical documents. This is achieved through use of natural language processing techniques and highly specialized medical knowledge bases such as Unified Medical Language System.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.25-33
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• 2006

For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.34-39
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• 2021

Collaborative ontology construction is the latest trend in developing ontologies. In this technique domain specialists and ontologists need to work together. Because of the complexity associated with ontology construction, it's done in an iterative and incremental fashion. After each iteration, an ontology increment will be produced. Current ontology increment is always an enhanced version of the previous increment. Each ontology increment has to be verified for its accuracy. Domain specialists' contribution is very significant in accomplishing this necessity. Unfortunately, non-computing domain specialists (i.e. medical doctors, bankers, lawyers) are illiterate on semantic concepts. Therefore, validating the accuracy of the ontology increment is a complex hurdle for them. This research proposes verbalization approach to address this complexity.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• 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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.730-733
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• 2004

Recently XML (eXtensible Markup Language) is becoming the standard for exchanging the documents on the web. And as the amount of information is increasing because of the development of the technique in the Internet, semantic web is becoming to appear for more exact result of information retrieval than the existing one on the web. Ontology which is the basis of the semantic web provides the basic knowledge system to express a particular knowledge. So it can show the exact result of the information retrieval. Ontology defines the particular concepts and the relationships between the concepts about specific domain and it has the hierarchy similar to the taxonomy. In this paper, we propose the generation of semi-automatic ontology based on XML documents that are interesting to many researchers as the means of knowledge expression. To construct the ontology in a particular domain, we suggest the algorithm to determine the domain. So we determined that the domain of ontology is to extract the information of movie on the web. And we used the generalized association rules, one of data mining methods, to generate the ontology, using the tag and contents of XML documents. And XTM (XML Topic Maps), ISO Standard, is used to construct the ontology as an ontology language. The advantage of this method is that because we construct the ontology based on the terms frequently used documents related in the domain, it is useful to query and retrieve the related domain.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1552-1559
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• 2006

In a web environment, similar information exists in many different places in diverse formats. Even duplicate information is stored in the various databases using different terminologies. Since most information serviced in the current World Wide Web however had been constructed before the advent of ontology, it is practically almost impossible to construct ontology for all those resources in the web. In this paper, we assume that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and existing RDBMS tables for semantic retrieval. In the processing of extracting a local ontology, some problems such as losing domain in formation can occur since the correlation of domain ontology has not been considered at all. To prevent these problems, we propose an instance-based matching which uses relational information between RDBMS tables and relational information between classes in domain ontology. To verify the efficiency of the method proposed in this paper, several experiments are conducted using the digital heritage information currently serviced in the countrywide museums. Results show that the proposed method increase retrieval accuracy in terms of user relevance and satisfaction.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.410-420
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• 2001

A primitive conceptualization is defined as the set of all intended situations. A non-primitive conceptualization is defined as the set of all the pairs every of which consists of an intended knowledge system and the set of all the situations admitted by the knowledge system. The reality of a domain is considered as the set of all the situation which have ever taken place in the past, are taking place now and will take place in the future. A conceptualization is defined as precise if the set of intended situations is equal to the domain reality. The representation of various elements of a domain ontology in a model of the ontology is considered. These elements are terms for situation description and situations themselves, terms for knowledge description and knowledge systems themselves, mathematical terms and constructions, auxiliary terms and ontological agreements. It has been shown that any ontology representing a conceptualization has to be non-primitive if either (1) a conceptualization contains intended situations of different structures, or (2) a conceptualization contains concepts designated by terms for knowledge description, or (3) a conceptualization contains concept classes and determines properties of the concepts belonging to these classes, but the concepts themselves are introduced by domain knowledge, or (4) some restrictions on meanings of terms for situation description in a conceptualization depend on the meaning of terms for knowledge description.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.754-759
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• 2007

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

• 한국IT서비스학회:학술대회논문집
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• 2009.11a
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• pp.9-19
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• 2009

SCM은 시장의 변화를 신속하고 파악하고 IT 기술을 활용해 정보를 공유함으로써 변화에 보다 적극적으로 대처해 전체 Supply Chain의 이익을 높이고자 하는 전략적 사고라고 할 수 있다. SCM에서 파트너 선정은 장기적이고 전략적인 관점에서 이루어져야 하는 지식 집약적인 업무 Process이다. 본 연구는 SCM에서 파트너 선정의 절차를 Task Modeling을 통해 재사용 가능한 Knowledge-base를 개발하는 것이다. 이를 위해, 첫 번째로 전문가의 문제 해결 과정을 분석해 문제 해결 과정을 대상으로 한 Problem-Solving Ontology(Task Ontology)를 도출하고, 두 번째로 문제 해결 과정에 필요한 Domain Knowledge를 추출해 파트너 선정 문제 해결에 필요한 Domain Ontology를 개발한다. 끝으로 Problem-Solving Ontology와 Domain Ontology를 Protege를 통해 구현하고자 한다.