• 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.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.979-991
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• 2016

Measuring nation images was a challenging task when employing offline surveys was the only option. It was not only prohibitively expensive, but too much time-consuming and therefore unfitted to this rapidly changing world. Although demands for monitoring real-time nation images were ever-increasing, an affordable and reliable solution to measure nation images has not been available up to this date. The researcher in this study developed a semi-automatic ontology construction algorithm, named "double-crossing double keyword collection (or DCDKC)" to measure nation images from Wikipedia in real-time. The ontology, WikiOnto, can be used to reflect dynamic image changes. In this study, an instance of WikiOnto was constructed by applying the algorithm to the big-three exporting countries in East Asia, Korea, Japan, and China. Then, the numbers of page views for words in the instance of WikiOnto were counted. A collection of the counting for each country was compared to each other to inspect the possibility to use for dynamic nation images. As for the conclusion, the result shows how the images of the three countries have changed for the period the study was performed. It confirms that DCDKC can very well be used for a real-time nation-image monitoring system.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.154-157
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• 2011

본 연구는 2인의 전문의와 함께 의료 문헌의 초록을 분석하여 의료문서에서의 절차적 지식을 모델링하고 텍스트 마이닝 기법을 적용하여 절차적 지식을 추출하는 방법론에 대해 기술한다. 절차적 지식은 목적과 해법의 묶음으로, 해법은 다시 단위 절차 지식의 네트워크로 정의 하였고, 목적과 해법 정보 추출과 단위 절차 지식의 구성요소인 대상/행위/방법 개체를 인식하기 위해, 품사태깅, 구문분석, 술어-논항구조(Predicate-Argument Structure), 온톨로지 용어 매핑 정보 등에 기반한 기계학습 방법을 사용하였다. 실험을 위해 전문의와 함께 위함과 척추질환에 대한 1309 문서에 절차적 지식 태깅을 수행하였고, 이 문서 집합을 기반으로 목적/해법 추출 작업과 단위 절차 지식(대상질병/행위/적용방법) 추출 실험을 수행하여, 각각 82% 와 63%의 F-measure 값을 얻을 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.221-225
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• 2007

본 논문은 시나리오를 입력하여 자동으로 애니메이션을 저작하는 기술에 관한 것으로서 시나리오 내용에서 매핑 되는 3D 데이터를 온톨로지 기법을 통해 추출할 수 있도록 한다. 또한 Flow Chart 그래픽 유지 인터페이스를 통한 직관적이고 손쉬운 입력방식과 애니메이션 분기 및 흐름 제어를 이용한 인터액티브 애니메이션을 제작할 수 있다. 본 기술을 활용하여 비전문가도 원하는 애니메이션 콘텐츠를 기존 애니메이션 콘텐츠 제작 방식보다 쉽고 간편하게 제작할 수 있도록 한다.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.151-157
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• 2008

This study aims to construct the aged portal sites based on multimedia DB on the basis of request for systematic collection and management of the aged-related specific information which are spreading and construct Multimedia Information System for the Aged by developing digital contents to offer the aged-related information. It also tries to construct ontology based information repository for the aged that includes on/off-line. It extracts semantic relationship of each information by analysing the aged information, knows the hierarchical structure of each vocabulary, and designs and constructs an ontology based repository by designing function of each agent through that. It has also developed a variety of information and digital contents, constructed a systematic multimedia DB for the aged welfare homes, developed web framework which makes automatic registration of the aged welfare homes possible, and designed in order to support the use state of enterprises/homes and statistics state.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.548-557
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• 2010

In this paper, we propose a semi-automatic modeling approach of ontology to annotate VOD to realize the IPTV's intelligent searching. The ontology is made by combining partial tree that extracts hypernym, hyponym, and synonym of keywords related to a service domain from WordNet. Further, we add to the partial tree new keywords that are undefined in WordNet, such as foreign words and words written in Chinese characters. The ontology consists of two parts: generic hierarchy and specific hierarchy. The former is the semantic model of vocabularies such as keywords and contents of keywords. They are defined as classes including property restrictions in the ontology. The latter is generated using the reasoning technique by inferring contents of keywords based on the generic hierarchy. An annotation generates metadata (i.e., contents and genre) of VOD based on the specific hierarchy. The generic hierarchy can be applied to other domains, and the specific hierarchy helps modeling the ontology to fit the service domain. This approach is proved as good to generate metadata independent of any specific domain. As a result, the proposed method produced around 82% precision with 2,400 VOD annotation test data.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.23-33
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• 2014

The development of the information retrieval field is evolving to the research field searching accurately for the information from thing finding rapidly a large amount of information. Personalization and the semantic web technology is a key technology. The automatic indexing technology about the web document and throughput go beyond the research stage and show up as the practical service. However, there is a lack of research on the document information retrieval field about the attached document type of except the web document. In this paper, we illustrate about the method in which it analyzed the text content of the unstructured documents prepared in the text, word, hwp form and it how to construction OWL ontology. To build TBox of the document ontology and the resources which can be obtained from the document is selected, and we implement with the system in order to utilize as the instant of the constructed document ontology. It is effectually usable in the information retrieval and document management system using the semantic technology of the correspondence document as the ontology automatic construction of this kind of the unstructured documents.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.43-53
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• 2014

In this paper, we propose an ontology-based approach to measuring degree-of-interest in country by analyzing wikipedia usage data. First, we developed the degree-of-interest ontology called DOI ontology by extracting concept hierarchies from wikipedia categories. Second, we map the title of frequently edited articles into DOI ontology, and we measure degree-of-interest based on DOI ontology by analyzing wikipedia page views. Finally, we perform chi-square test of independence to figure out if interesting fields are independent or not by country. This approach shows interesting fields are closely related to each country, and provides degree of interests by country timely and flexibly as compared with conventional questionnaire survey analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.