• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.353-356
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• 2019

본 논문은 Universal conceptual cognitive annotation(보편 개념 인지 주석, 이하 UCCA)를 한국어에 적용하는 방안에 대해 제시하였다. 우선 기존의 한국어 의미 분석 체계들의 장단점을 살펴본 뒤, UCCA가 가지고 있는 상대적인 장점들을 소개하였다. UCCA는 모든 언어에 대하여 일관적인 기술을 하려는 Meaning representation framework의 하나로, 보편언어적인 의미 분석 체계를 가지고 있다. 본고는 주석 단위와 문법적 요소의 관점에서 한국어의 특성을 반영하여 UCCA를 한국어에 적용하는 방안을 검토하였다.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.739-745
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• 2014

In this paper, an evaluation of intelligent CCTV system is proposed with recording and implementation video and video DB. Videos for evaluation are recorded by dividing far, mid and near zone. Video DB has video recording information, detection area, and ground truth in XML format. A video annotation tool is proposed to make ground truth effectively in this paper. A video annotation tool writes ground truths of videos and includes evaluation comparing system alarms with ground truths.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.11-18
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• 2008

One of important Issues in computer graphics field is to communicate among users in virtual world like secondlife. However, in 3D virtual world, users' needs to wish to build their own contents in 3D virtual space are rising, similarly, users produce own homepage and animation, and leave writing in notice board. In this paper, we tried to achieve this by introducing semantic annotation object concept, which is a kind of annotation method in 3D virtual world. User can retrieve an 3D object by searching corresponding annotation data. This method can build semantic 3D virtual world and enable users to search 3D objects by integrating 3D object and 2D semantic multimedia information. Also, through a comparison experiment with proposal system and general 3D virtual world. the performance of proposed system is evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1071-1092
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• 2014

Annotating images with tags that describe the content of the images facilitates image retrieval. However, this task is challenging for both humans and computers. In response, a new approach has been proposed that converts the manual image annotation task into CAPTCHA challenges. However, this approach has not been widely used because of its weak security and the fact that it can be applied only to annotate for a specific type of attribute clearly separated into mutually exclusive categories (e.g., gender). In this paper, we propose a novel image annotation CAPTCHA scheme, which can successfully differentiate between humans and computers, annotate image content difficult to separate into mutually exclusive categories, and generate verified test images difficult for computers to identify but easy for humans. To test its feasibility, we applied our scheme to annotate images of human faces with their age groups and conducted user studies. The results showed that our proposed system, called AgeCAPTCHA, annotated images of human faces with high reliability, yet the process was completed by the subjects quickly and accurately enough for practical use. As a result, we have not only verified the effectiveness of our scheme but also increased the applicability of image annotation CAPTCHAs.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.66-71
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• 2007

멀티미디어 데이터에 대한 효율적인 검색을 지원하기 위해 제정된 MPEG7이나 TV-AnyTime 등의 표준들은 XML을 사용하여 Metadata를 효과적으로 표현할 수 방법을 제시하고 있다. 플랫폼에 독립적으로 사용가능하다는 XML의 강점에도 불구하고 Text 방식으로 데이터를 저장하기 때문에 보안에 취약할 수밖에 없으며, 대용량의 자료 처리에도 문제점을 드러낸다. 이를 보완하기 위하여 XML 문서를 RDBMS에 저장하는 방법들이 제안되고 있는데, 기존의 Model Mapping이나 Structure Mapping의 경우 노드 검색을 위해 Traversing을 할 경우 많은 조인이 필요하기 때문에 한정된 메모리와 낮은 처리능력을 갖춘 임베디드 멀티미디어 플랫폼에서는 비효율적일 수밖에 없다. 본 논문에서는 MPEG7 Metadata를 RDBMS에 저장하고, 이를 검색할 때, 조인의 횟수를 최소화할 수 있는 저장 모델을 제안하고 있다. 부모, 자식, 형제간의 노드를 효율적으로 검색할 수 있도록 path MetaSchema를 제안함으로써, 최소 1번의 검색으로 필요한 노드 정보들을 추출할 수 있도록 하였다. 그리고 Annotation 작성시에 XML의 Attribute와 Element로 삽입하였기에, 기존의 방법에서 Annotation을 분석하기 위해 필요했던 Annotation 파싱을 제거하고, SAX나 DOM을 사용할 수 있도록 제안함으로써, Annotation의 정보에 대한 접근이 효율적으로 개선되었다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.35-44
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• 2008

In this paper, we present an EST sequence annotation system based on Service Oriented Architecture, called SeqWeB. We developed the web services of eight applications (Phred, cross_match, RepeatMasker, TGICL, ICAtools, CAP3, Phrap and Blast) which are located in sequence annotation process and integrated the web services through BFEL. SeqWeB uses an XML file format for data input and output to maximize interoperability between each application. SeqWeB can be extended or modified easily through some modification such as insertion, deletion and replacement because service-oriented architecture allows loose coupling between applications.

• Genomics & Informatics
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• v.19 no.3
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• pp.23.1-23.7
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• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.271-287
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• 2013

The rapid growth and dissemination of touch-based mobile devices such as smart phones and tablet PCs, gives numerous benefits to people using a variety of multimedia contents. Due to its portability, it enables users to watch a soccer game, search video from YouTube, and sometimes tag on contents on the road. However, the limited screen size of mobile devices and touch-based character input methods based on this, are still major problems of searching and tagging multimedia contents. In this paper, we propose WalkieTagging, which provides a much more intuitive way than that of previous one. Just like any other previous video tagging services, WalkieTagging, as a voice-based annotation service, supports inserting detailed annotation data including start time, duration, tags, with little effort of users. To evaluate our methods, we developed the Android-based WalkieTagging application and performed user study via a two-week. Through our experiments by a total of 46 people, we observed that experiment participator think our system is more convenient and useful than that of touch-based one. Consequently, we found out that voice-based annotation methods can provide users with much convenience and satisfaction than that of touch-based methods in the mobile environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2650-2662
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• 2012

Due to the semantic gap issue, the performance of automatic image annotation is still far from satisfactory. Active learning approaches provide a possible solution to cope with this problem by selecting most effective samples to ask users to label for training. One of the key research points in active learning is how to select the most effective samples. In this paper, we propose a novel active learning approach based on sparse graph. Comparing with the existing active learning approaches, the proposed method selects the samples based on two criteria: uncertainty and representativeness. The representativeness indicates the contribution of a sample's label propagating to the other samples, while the existing approaches did not take the representativeness into consideration. Extensive experiments show that bringing the representativeness criterion into the sample selection process can significantly improve the active learning effectiveness.