• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.97-100
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• 2009

인터넷에는 다양하고 많은 정보들이 담겨져 있다. 이 많은 정보들 중에서 사용자가 정말로 필요로 하는 정보를 기계로 추출해 내기 위해서 시맨틱 웹이라는 기술이 제안 되었다. 시맨틱 웹의 구현을 위해서는 기계가 해석할수 있는 데이터들이 필요한데 이것은 시맨틱 어노테이션을 통해서 얻어낼수 있다. 대부분의 시맨틱 어노테이션 시스템들은 영어로 작성된 문서들에 포커스를 두고 개발되었다. 한국어와 같은 교착어를 처리할수 있는 시스템들은 드물다. 본 논문에서는 시맨틱 어노테이션에 대해서 자세히 설명하고 한국어 시맨틱 어노테이션 시스템을 개발하는데에 어떤 언어적인 특징을 고려해야 하는지 살펴본다. 그리고 국외에서 개발된 한국어 시맨틱 어노테이션 시스템 EXCOM을 예제로 소개하겠다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.523-525
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• 2004

기존의 웹 컨텐츠를 휴대폰이나 poA등과 같은 개인용 단말기에 표현하기에는 단말기 성능상의 제약(낮은 CPU 성능, 작은 출력 화면, 입출력 방법의 단순함 등)이 따르게 되므로 컨텐츠 변환의 과정이 필요하게 된다. 트랜스코딩이감 기존의 웹 컨텐츠를 단말기의 환경에 따라 적합한 형태로 변환하는 것을 의미하며, HTML 문서의 레이아웃 정보를 이용하여 변환하는 연구가 다양하게 이루어져 왔다. 본 논문에서는 사용자 의견을 반영한 XML문서의 정확한 트랜스 코딩을 위하여 시맨틱 어노테이션 기법을 제안한다. XML 문서의 트랜스코딩에는 IPTC(International Press Telecommunications Council)에서 정한 NewsML을 기반으로 하였으며, 본 논문에서 제안하는 트랜스코딩 프레임워크는 크게 3단계로 나뉘어 진다. 어노테이션 생성 및 인식, 어노테이션의 구조 정보를 활용한 페이지 생성 및 페이지 앱 구성, 디바이스에 따른 페이지의 변환으로 구성된다. 향후 연구로는 어노테이션과 페이지 생성 기법을 통해 생성된 XML 문서를 CC/PP를 이용하여 poA나 휴대폰 등의 시스템에 적합하게 변환하는 기법 등이 요구된다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.1-11
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• 2010

The success of semantic web depends largely on the semantic annotation which systematizes knowledge for the construction and production of ontology. Therefore, the efficiency of semantic annotation is very important in order to change many knowledge expressions and generate into ontology instances. In this paper, we presents a generation system of rule-based ontology instances which are produced accurately and efficiently via semantic annotation in conventional web sites. In conventional studies, the manual process is necessary for finding relevant information, comparing it with ontology, and entering information. We propose a new method that manages keyword data regarding extracted information and rule information separately. Thus, it is quite practical to extract information efficiently from various web documents by adding a small number of keywords and rules. The proposed method shows the possibility of ontology instance generation which reuses the rules and keywords from the various websites.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.67-76
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• 2011

Recently, researches for semantic annotation methods which represent and search objects included in video data, have been briskly activated since video starts to be popularized as types for interactive contents. Different location data occurs at each frame because coordinates of moving objects are changed with the course of time. Saving the location data for objects of every frame is too ineffective. Thus, it is needed to compress and represent effectively. This paper suggests two methods; the first, ontology modeling for moving objects to make users intuitively understandable for the information, the second, to reduce the amount of data for annotating moving objects by using cubic spline interpolation. To verify efficiency of the suggested method, we implemented the interactive video system and then compared with each video dataset based on sampling intervals. The result follows : when we got samples of coordinate less than every 15 frame, it showed that could save up to 80% amount of data storage; moreover, maximum of error deviation was under 31 pixels and the average was less than 4 pixels.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.100-104
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• 2010

Recently with advent of Web 2.0, RESTful Web Services are becoming increasing trend to emphasize Web as platform. There are already many services and the number of service increases in very fast pace. So it is difficult to find the service what we want by keyword based search. To solve this problem, we developed the search method using sem antic technologies about RESTful Web Services. For that, first we define the system structure and model the description format based on the integrated search system for OpenAPIs, and then we add Semantic Markup (tagging, semantic annotation) on the HTML description pages. Next we extract RDF document from them and store it in service repository. Based on the keywords that are extended by means of ontology, the developed system provides more purified and extended results than similarity-based keyword searching system.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.576-579
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• 2010

콜센터의 고객문의는 복잡하여 기존 검색 시스템으로는 고객의 문제점을 신속하게 찾아 상담에 적용하는데 문제가 많았다. 온톨로지를 구축하고 시맨틱 검색을 제공할 경우 보다 보다 좋은 검색 기능을 제공할 것으로 기대되나 콜센터의 상담지식은 내용이 매우 복잡하여 그 텍스트의 내용을 완벽하게 온톨로지로 표현하는 것은 쉽지 않았다. 본 논문에서는 온톨로지 기반으로 구축된 지식베이스의 데이터 검색과 함께 그와 가장 관련성이 높은 문서를 출력하기 위해 문서를 온톨로지와 링크하여 어노테이션하는 방법을 제안한다. 본 시스템을 적용한 상담에서 상담원들의 생산성이 향상되고 고객 만족도를 높이는 결과를 확인했다.

• Journal of KIISE
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• v.42 no.5
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• pp.580-590
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• 2015

Recently, the issue of efficient power management in datacenters as a part of green computing has gained prominence. For realizing efficient power management, effective power monitoring and analysis must be conducted for servers in a datacenter. However, an administrator should know the exact structure of the datacenter and its associated databases, and is required to analyze relationships among the observed data. This is because according to previous monitoring approaches, servers are usually managed using only databases. In addition, it is not possible to monitor data that are not indicated in databases. To overcome these drawbacks, we proposed an ontology-based monitoring approach. We constructed domain ontology for management servers at a datacenter, and mapped observed data onto the constructed domain ontology by using semantic annotation. Moreover, we defined query creation rules and server state rules. To demonstrate the proposed approach, we designed an ontology based monitoring system architecture, and constructed a knowledge system. Subsequently, we implemented the pilot system to verify its effectiveness.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.