• Journal of KIISE:Software and Applications
• /
• v.30 no.5_6
• /
• pp.559-569
• /
• 2003

Annotation is used for inscribing personal opinion, explanation, and summary. Various methods for processing annotation efficiently in digital document environments are being studied. However, previous studies placed much emphasis on function of annotation, so either they did not support Intuitive paper-based input interface or the systems that support it still have low reusability problems, because relation between annotation and original document are not explicit. Thus, in our study, we define context-based annotation modeling for digital document environments, and suggest annotation interface based on the modeling. To design annotation model, we define annotation types, context information of document, and relationship between annotation and original document. Also, a system based on the modeling is implemented to support pen-based annotation and annotation DTD. As a result, unlike previous studies, it is possible to explicitly define context-based annotation in pen-based input environments. We present various functions using the modeling and various possibilities of application.

• Journal of Korea Multimedia Society
• /
• v.6 no.4
• /
• pp.565-575
• /
• 2003

This paper proposed context based annotation model and annotation ambiguity correction methods. The proposed model provides various annotation types, semantic models, and pen-based free drawing interface. Annotation correction method that is specifically based on the context which includes various textual and structure information between free-form marking and annotation. Also, interface for XML environment using the proposed model and correction methods is proposed and possibilities of application is looked at. The results from the implementation of the proposed method show that the annotated areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment

• Journal of KIISE:Software and Applications
• /
• v.30 no.9
• /
• pp.850-861
• /
• 2003

When creating annotation information in a free~form environment, ambiguity arises during the analysis stage between geometric information and the annotations. This needs to be resolved so that the accurate creation of annotation information in a free-form annotation environment is possible. This paper identifies and analyzes the ambiguities, specifying methods that are tailored to each of the various contexts that can cause conflicts with free-form marking in a XML-based annotation environment. The proposed general method is based on context which includes various textual and structure information between free-form marking and the annotations themselves. The context information used is expressed in XML based DTD, within the paper. The results are printed and shared through a system specifically implemented for this study. The results from the implementation of the Proposed method show that the annotated areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2001.11a
• /
• pp.602-606
• /
• 2001

전자책은 기존 종이 문서에 비하여 다양한 기능 및 장점을 제공할 수 있기 때문에 현재 다양한 연구 및 서비스가 제공되고 있다. 또한 전자책 환경에서의 정보 공유 및 검색과 같은 다양한 활용을 위해서는 반드시 Annotation 지원이 가능하여야 하며 이에 대한 정확한 Annotation 정의가 요구된다. Annotation이란 일반적으로 문서의 주제 및 내용에 관한 해설, 설명, 그리고 강조를 목적으로 추가되는 문장 또는 텍스트를 의미한다. 그러나 기존 전자책 환경에서의 Annotation과 관련된 연구에서는 이에 대한 심도있는 연구 결과가 미비한 실정이다. 이에 본 연구에서는 전자책 환경을 위한 Context 기반 Annotation Modeling을 정의하고 이를 활용한 인터페이스를 제안한다. 현재 전자책 환경은 대부분 XML에 기반하고 있으며 이에 본 논문에서는 구조정보와 컨텐츠, 그리고 Annotation간의 관계 및 이를 활용하기 위한 모델링을 제시한다. 또한 모델링 정보를 이용한 다양한 장점 및 환용이 가능한 시스템을 구현하였다. 그 결과 본 연구에서는 기존 연구와는 달리 Context 기반 Annotation의 정확한 정의가 가능하며 이를 활용한 다양한 기능을 제공하는 동시에 앞으로의 응용 가능성을 제시하고 있다.

• Journal of The Korean Association of Information Education
• /
• v.10 no.2
• /
• pp.219-226
• /
• 2006

For the accurate creation of annotation information in a free-form annotation environment, the ambiguity that arises in the analysis stage between the geometric information and annotations needs to be resolved. Therefore, this This paper identifies, analyzes, and proposes presents solutions methods for the ambiguity that can occur between free-form marking and various contexts in XML-based annotation environment. The proposed method is based on context which includes various textual and structure information between free-form marking and annotated part. The proposed method show that the annotated portions areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment. This study can be effectively applied to eLearning, Cyber-Class, and IETM

• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.926-930
• /
• 2006

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

• Journal of Korea Multimedia Society
• /
• v.19 no.8
• /
• pp.1498-1504
• /
• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Educational Technology International
• /
• v.17 no.1
• /
• pp.87-116
• /
• 2016

In this research, we designed a teacher professional development (PD) program where a small group of mathematics teachers could share, reflect on, and discuss their pedagogical knowledge and practices of ICT-integrated lessons, using a video annotation tool called DIVER. The main purposes of this paper are both micro and macro: to examine how the teachers were engaged in the meaning-making process in a video-based PD (micro); and to derive implications about how to design effective video-based teacher PD programs toward a teacher community of practices (macro). To examine teachers' meaning-making in the PD sessions, discourse data from a series of 10 meetings was segmented into idea units and coded to identify discourse patterns, focusing on (a) participation levels, (b) conversation topics, and (c) conversation depth. Regarding the affordance of DIVER, discourse patterns of two meetings, before and after individual annotation with DIVER were compared through qualitative vignette analysis. Overall, we found that the teacher discourse shifted the focus from surface features to deeper pedagogical issues as the PD sessions progressed. In particular, the annotation function in DIVER afforded the teachers to exercise descriptive analyses of video clips in a flexible manner, thereby helping them cognitively prepared to take interpretative and evaluative stances in face-to-face discussions with colleagues. In conclusion, deriving from our research experiences, we discuss the possibilities and challenges of designing video-based teacher PD in a school context.

• Journal of KIISE:Software and Applications
• /
• v.32 no.7
• /
• pp.650-662
• /
• 2005

A robust repositioning method is required for annotations to always maintain proper positions when original documents were modified. Robust anchoring in the XML document provides better anchoring results when it includes features of structured documents as well as annotated texts. This paper proposes robust annotation anchoring method in XML document. To do this, this work presents annotation information as logical structure trees, and creates candidate anchors by analyzing matching relations between the annotation and document trees. To select the appropriate candidate anchor among many candidate anchors, this work presents several anchoring criteria based on the textual and label context of anchor nodes in the logical structure trees. As a result, robust anchoring is realized even after various modifications of contexts in the structured document.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.6
• /
• pp.267-275
• /
• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.