• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1415-1418
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• 2011

최근 웹상에 이용 가능한 RESTful 웹 서비스들의 수가 급격하게 증가됨에 따라 사용자들이 적합한 웹 서비스를 찾는 것은 매우 중요한 이슈로 대두되었다. 그러나 기존의 키워드 기반 검색 방법은 나쁜 재현율과 나쁜 정확률 때문에 문제가 많다. 본 논문에서는 매개변수 클러스터링 기법에 패턴 분석 기법을 추가한 하나의 새로운 시맨틱 온톨로지 구축 방법을 제안한다. 이를 통해 온톨로지를 자동 구축하여 시맨틱 정보의 주석처리 부담을 줄일 수 있고, 보다 효율적인 웹 서비스 검색을 지원한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.235-236
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• 2016

The importance of construction management has been increasing due to the fact that complex construction projects blend several different industries depending on the traits of the construction. This research was conducted to search for a method to enhance efficiency in cost management of construction project and meet the need for reusability of accumulated construction information. The process of detailed estimation and methodology for using standard unit price information has been developed to strengthen the interoperability in cost information by utilizing a standard classification system. The concept of ontology is proposed as a method of connecting construction information based on a standard breakdown structure to increasing the connectivity of the cost information in the construction project. Therefore, construction information knowledge framework is developed in order to improve the efficiency of the detailed estimation work process.

• Korean Linguistics
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• v.48
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• pp.223-268
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• 2010

The purpose of this paper is to build a semantic networks of the 'cooking class' verb (based on 'CoreNet' of KAIST). This proceedings needs to adjust the concept classification. Then sub-categories of [Cooking] and [Foodstuff] hierarchy of CoreNet was adjusted for the construction of verb semantic networks. For the building a semantic networks, each meaning of 'Cooking verbs' of Korean has to be analyzed. This paper focused on the Korean 'heating' verbs and 'non-heating'verbs. Case frame structure and argument information were inserted for the describing verb information. This paper use a Propege 3.3 as a tool for building "cooking verb" semantic networks. Each verb and noun was inserted into it's class, and connected by property relation marker 'HasThemeAs', 'IsMaterialOf'.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.96-97
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• 2021

In the 4th Industrial Revolution and changes in the construction industry market, the importance of information management is becoming more emphasized. For efficient use of information, construction data must be collected, processed and analyzed more quickly and accurately, depending on the purpose of the project. Thus, data could be utilized as integrated knowledge. However, there is a limit to searching or managing construction information produced in various formats over the entire life cycle by index words. Therefore, this study proposes a construction information integrated management plan that reflects the characteristics of the construction industry by applying the OWL concept. For this, as an initial study, an architectural object of small size and clear features was needed. Therefore, a construction information management study using OWL was conducted for Korean traditional architectural style houses (Hanok) which has these characteristics.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.165-187
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• 2018

Despite repeated efforts to develop a methodological foundation for assembling collaborative authority data in South Korea, issues such as the establishment of a standard authority model and standard authority construction as well as the reconfiguration of existing entities in authority building have prevented such research from generating a cooperative push for nation-wide authority data and progressing toward concrete implementation. The formulation of a collaborative and well-utilized collection of national authority data accordingly calls for 1) a practical approach to supporting both established authority data contributors and newly organized avenues of mutual participation in authority building, 2) committed involvement on the part of national institutions capable of providing the project with sustained assistance, and 3) a standard identification system which allows multiple organizations to merge their data. This study addresses the challenges of the current environment by taking stock of the key components necessary for the creation of collaborative authority data and using a Semantic Web-based interoperable VIVO ontology model to propose a viable national authority data framework.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.596-603
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• 2015

A concept network is an essential knowledge base for semantic search engines, personalized search systems, recommendation systems, and text mining. Recently, studies of extending concept representation using external ontology have been frequently conducted. We thus propose a new way of building 3-dimensional text model-based concept networks using the world knowledge-level Wikipedia ontology. In fact, it is desirable that 'concepts' derived from text documents are defined according to the theoretical framework of formal concept analysis, since relationships among concepts generally change over time. In this paper, concept networks hidden in a given document collection are extracted more reasonably by representing a concept as a term-by-document matrix.

• Journal of KIISE
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• v.42 no.3
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• pp.295-306
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• 2015

MOnCa2 is a framework for building intelligent smartphone applications based on smartphone sensors and ontology reasoning. In previous studies, MOnCa determined and inferred user situations based on sensor values represented by ontology instances. When this approach is applied, recognizing user space information or objects in user surroundings is possible, whereas determining the user's physical context (travel behavior, travel destination) is impossible. In this paper, MOnCa2 is used to build recognition models for travel behavior and routes using smartphone sensors to analyze the user's physical context, infer basic context regarding the user's travel behavior and routes by adapting these models, and generate high-level context by applying ontology reasoning to the basic context for creating intelligent applications. This paper is focused on approaches that are able to recognize the user's travel behavior using smartphone accelerometers, predict personal routes and destinations using GPS signals, and infer high-level context by applying realization.

• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.4
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• pp.362-366
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• 2013

We are building an Korean Medicine ontology and disassembling indication terms of medicinal materials and formulas. When we disassemble these terms, an expert can disagree about another expert's result, so participants have to consider another opinion and verify each other concurrently. To achieve this, we have developed a web-based tool that support users in refining terms, disassembling them into the minimum meaning efficiently. With this tool, plural participants refer to each other and make use of this as a verification method. This would have enabled participants to achieve consensus. Due to the nature of the traditional Korean Medicine knowledge which have rich implications and is complicated,E there would be a various result of refinement, disassembly, analysis and another processing. This tool assists users in minimizing the differences and maintaining objectivity by agreement. We have refined and analyzed 4,756 terms from materials and formulas indication in Korean Medicine ontology using this tool. And we concluded that disassembled data increases the percentage of linkage between diseases and medicinal treatments and established an infrastructure for the extensible knowledge.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.101-119
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• 2003

Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged, methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.1-14
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• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.