• Asian review of World Histories
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• v.4 no.1
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• pp.125-132
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• 2016

This paper, as a conlcusion to this special issue, presents the future work that is being carried out at NTU Singapore in collaboration with Microsoft Research and Microsoft Azure for Research. For our research team the real frontier research in world histories starts when we want to use computers to structure historical information, model historical narratives, simulate theoretical large scale hypotheses, and incent world historians to use virtual assistants and/or engage them in teamwork using social media and/or seduce them with immersive spaces to provide new learning and sharing environments, in which new things can emerge and happen: "You do not know which will be the next idea. Just repeating the same things is not enough" (Carlo Rubbia, 1984 Nobel Price in Physics, at Nanyang Technological University on January 19, 2016).

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.631-633
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• 2005

유비쿼터스 시대가 다가오면서, 많은 사람들은 모르는 장소에서 자신의 위치와 목적지까지의 경로에 대한 정보를 알고 싶어할 것이다. 기존의 네비게이션(navigation)을 위한 비전기술은 고차원과 저차원 특징값을 이용하였다. 텍스춰 정보, 색상 히스토그램과 같은 저차원 특징값은 영상의 특징을 정확하게 표현하기 어려우며, 마커와 같은 고차원 정보는 실험환경을 구축하는데 어려움이 있다. 우리는 기존 저/고차원의 특징값 대신, 영상의 특징을 표현하고 인덱싱(indexing)하기 위한 유용한 정보를 많이 포함하고 있으며, 실제환경에서 널리 분포되어있는 중차원 특징값인 문자영상을 이용한다. 문자영상추출은 MLP(Multi-layer perceptron)와 CAMShift알고리즘을 결합한 방법을 이용하며, 서로 다른 장소지만 같은 문자를 가진 곳에서 인식을 수행하기 위해 문자영상의 크기와 기울기를 기반으로 한 영상 검색공간을 대상으로 영상매칭을 수행한다. 실험에서 문자영상을 포함하는 직사각형 검색공간으로 인해 다양한 크기와 기울기에서 높은 인식률을 보이며, 간단한 계산으로 빠른 수행시간을 가진다.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.311-320
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• 2007

In this paper, an efficient detection algorithm of an anchor shot in news video is presented. We observed the audio visual characteristics of news video and proposed several low level features which are appropriate for detecting an anchor shot in news video. The overall structure of the proposed algorithm is composed of 3 stages: the pause detection, the audio cluster classification, and the matching with motion activity stage. We used the audio features as well as the motion feature in order to improve the indexing accuracy and the simulation results show that the performance of the proposed algorithm is quite satisfactory.

• Journal of Korean Library and Information Science Society
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• v.30 no.2
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• pp.179-198
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• 1999

The scope and the magnitude of change that are occurring in libraries today are exciting and the new developments in information technology challenging. A change in vision as well as activities and operations is required. Librarians need to make full use of information and multimedia technology to support this greatly expanded teaching venture. During the period of the 1st to 5th conference of Korean Society for Information Management produces 199 articles. The articles composed of 25 sub subjects of the knowledge of the library and information science. Some of the interesting sub-subjects were as follows: Information retrieval, Indexing, Classification, Library management, Information service, Cataloging and Digital library. The professional librarians pointed out the essential curricula of the library and informations science education. These are Introduction to Library Science, Organization of Information Resources, Information Retrieval, Multimedia technology, Information System, Library Management, Networks, Data Base, Indexing & thesaurus, Collection development, User Studies, New Media, Online Search.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.41-49
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• 2000

In this paper, we propose a new method of indexing and searching based on object-specific features at different semantic levels for video retrieval. A moving trajectory model is used as an indexing key for accessing the individual object in the semantic level. By tracking individual objects with segmented data, we can generate motion trajectories and set model parameters using polynomial curve fitting. The proposed searching scheme supports various types of queries including query by example, query by sketch, and query on weighting parameters for event-based video retrieval. When retrieving the interested video clip, the system returns the best matching event in the similarity order.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.3
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• pp.267-290
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• 2015

Diverse researches such as referring to classical literature for liberal arts courses, transformation of classical literature into cultural content and understanding classical literature through digital media have been engaged in an effort to spread the diachronic value of classical literature to the public in general, which should be based on clear understanding of authorship of classical literature. Thus this study aims to design ontology in order to establish knowledge structure of classical literature. For this purpose, the BIBFRAME model and OWL have been utilized while a variety of classical literature and related studies have been analyzed. This led to 19 classes of Work, Instance, Authority, and Annotation, instance, each of which has been provided with property and indexing examples. The classical literature ontology designed through this study is expected to serve as the foundation for development of a classical literature system in future.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.107-115
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• 2014

Recently, increased use of the internet resulted in generation of large and diverse types of data due to increased use of social media, expansion of a convergence of among industries, use of the various smart device. We are facing difficulties to manage and analyze the data using previous data processing techniques since the volume of the data is huge, form of the data varies and evolves rapidly. In other words, we need to study a new approach to solve such problems. Many approaches are being studied on this issue, and we are describing an effective design and development to build indexing engine of big data platform. Our goal is to build a system that could effectively manage for huge data set which exceeds previous data processing range, and that could reduce data analysis time. We used large SNMP log data for an experiment, and tried to reduce data analysis time through the fast indexing and searching approach. Also, we expect our approach could help analyzing the user data through visualization of the analyzed data expression.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.137-144
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• 2019

This paper deals with the longitudinal study on the supply & demand-side diversity of digital media service. The purpose of this study is to measure the diversity of contents supply and demand-side of digital media platform providers by longitudinal data and discuss the implication. In the approval and re-authorization of pay-TV broadcasters, there were attempts to measure diversity indicators as items to evaluate the publicness and public interest of broadcasting, but they are mainly limited to the method of measuring diversity in the short-term supply side. Thus researcher wants to confirm the evaluation of two aspects through this study. First, researcher proposes a demand-side measurement methodology that utilizes actual audience data from users, and second, a longitudinal evaluation methodology that evaluates long-term trends of diversity change. Researcher has secured the actual supply and demand data of the platform player and confirmed trends of longitudinal diversification indexing for 50 months from 2012 to 2017. Through this research, researcher expects that the supply and demand-side and the longitudinal diversity evaluation will be utilized in a balanced way of publicness and public interest evaluation of broadcasting.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.262-270
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• 2002

Although most image indexing schemes ate based on global image features, they have limited discrimination capability because they cannot capture local variations of the image. In this paper, we propose a new region-based image retrieval system that can extract important regions in the image using salient point extraction and image segmentation techniques. Our experimental results show that color and texture information in the region provide a significantly improved retrieval performances compared to the global feature extraction methods.