• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.313-316
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• 2016

온톨로지란 사물이나 개념의 속성이나 관계를 사람과 컴퓨터 모두 이해할 수 있는 형태로 표현한 모델로 정보검색, 인공지능, 소프트웨어 공학 등의 분야에서 많이 활용된다. 온톨로지에는 다양한 정보가 구조화되어 저장되어 있지만 일반적으로 온톨로지가 제공하는 그래프 형태의 데이터들은 사용자들이 직관적으로 이해하기가 힘들다. 따라서 본 논문에서는 온톨로지의 정보를 문장화하여 한국어 문서를 생성하는 시스템을 제안한다. 제안하는 시스템은 주제와 관련된 트리플을 추출하고 이를 문장정렬, 결합, 생성을 위한 정보가 담긴 템플릿을 생성한 뒤 한국어 문법에 맞게 문장을 생성한다. 또한 기존 연구에서 다루지 않았던 이벤트 온톨로지의 내용을 포함하여 문장을 생성한다. 두 온톨로지로부터 생성된 문장을 연결하여 주제어를 설명하는 하나의 문서를 작성한다.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.100-101
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• 2008

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.209-211
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• 2008

기술의 빠른 발전은 하드웨어와 소프트웨어의 다양한 결합방법으로 산업시스템을 정보기반 모델로 변경하고 있다. 엔지니어링시스템이 복잡해짐으로서 시스템의 에러를 줄이기 위한 다양한 시각화 모델 표현이 요구되고 연결관계를 구현하기위한 노력이 필요하다. 본 논문에서는 요구사항과 엔지니어링객체 사이에 추적고리로 디자인 컨셉을 삽입하여 외부 사용자 이벤트에 반응하고 추적고리를 설치하기 위한 시각적이고 효과적인 방법을 연구한다.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.117-127
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• 2007

As the value of the multimedia data is getting high, the study on the semantic recognition and retrieval about the multimedia information is strongly demanded. In this paper, we build the motion ontology and adopt it for representing the meaning of the moving objects in video data. By referencing the WordNet structure, we extend its semantic meaning based on the reclassification of motion verbs, which are used to represent the semantic meaning of moving objects. The represented information is receded in OWL/RDF(S). Here, we could expect the 'Is-A' and 'Equivalent' reasoning of the data as we use the ontologies. And the semantic representation about the moving objects is possible through the video annotation using ontology. And we tested the accuracy of the system comparing with the key-word based system. As a result, we could get the approximately 10% improvement of the system performance.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.2
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• pp.189-214
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• 2018

Archival description is considered as a creation and curation process, and the results of the descriptive records can be used for archival information service. Therefore, various archival descriptive standards provide essential guidelines for establishing a semantic and synthetic structure of the archival records. In this study, the structural aspects of the archival descriptive standards were analyzed and an experimental mapping between General International Standard Archival Description (ISAD(G)), the archival standard, and CIDOC Conceptual Reference Model (CIDOC CRM), the domain ontology of cultural heritage field was performed. The data structure of ISAD(G) is examined in advance and mapping was performed using Karma as a platform. It was thus concluded that there is a need to understand the ontology-based mapping method and the event-focused domain ontology. Moreover, developing a CIDOC CRM-compatible archival ontology and restructuring the legacy ISAD(G) are needed.

• Journal of Korean Library and Information Science Society
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• v.44 no.1
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• pp.5-26
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• 2013

Although organizing standardized metadata is important for effective management of cultural heritage information, current metadata are represented differently according to the properties of the resources or objectives of the organizations in which they are accumulated. This research compared 6 different metadata formats and created 18 data elements for constructing databases. A religious architecture heritage information database was constructed based on 72 historic religious architectures, each composing of three parts. An ontology based on religious architecture heritage information was designed using a revised CIDOC-CRM, and was developed with a semi-automated corpus program.

• Journal of KIISE
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• v.43 no.3
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• pp.370-379
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• 2016

Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.804-809
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• 2013

The current state monitoring system at a semiconductor manufacturing process is based on the manually collected sensor data, which involves limitations when it comes to complex malfunction detection and real time monitoring. This study aims to design a situation recognition algorithm to form a network over time by creating a domain ontology and to suggest a system to provide users with services by generating events upon finding risk factors in the semiconductor process. To this end, a multiple sensor node for situational inference was designed and tested. As a result of the experiment, events to which the rule of time inference was applied occurred for the contents formed over time with regard to a quantity of collected data while the events that occurred with regard to malfunction and external time factors provided log data only.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.475-481
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• 2014

Recently, it is used to apply various improved methods to determine the cause of traffic accidents. However, most of vehicle black box usually start to store the video information by an event trigger in case that the impact value at that time exceeds the threshold impact value as compared the threshold impact value saved in advance with the current impact value. there are problems with above method that a lot video information should be saved in the memory card of the vehicle black box, and the user should delete the unwanted video information every time because of unclassified video store. In this paper, we propose the ontology-based context aware algorithm that the vehicle black box recognize the situation, and then remove the video data with a low weighting factor by itself for efficient memory management.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.32-37
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• 2008

To ensure access to rapidly growing video collection, video indexing is becoming more and more important. In this paper, video ontology system for retrieving a video data based on a scene unit is proposed. The proposed system creates a semantic scene as a basic unit of video retrieval, and limits a domain of retrieval through a subject of that scene. The content of semantic scene is defined using the relationship between object and event included in the key frame of shots. The semantic gap between the low level feature and the high level feature is solved through the scene ontology to ensure the semantic-based retrieval.