• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.288-298
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• 2009

In this paper, we propose a scheme to associate content-based video signature with Universal Content Identifier (UCI) system of broadcast content for copyright identification and management. Note that content-based video signature can identify a previously distributed content since it is directly extracted from content itself without allocation process of identifier such as UCI. Thus, we design the schema of UCI application metadata, which provides a video signature in order to consistently maintain a systemic link between UCI and the video signature. Also, we present the scenarios of copyright identification, management and additional service, which are based on transmission and management mechanism of video signature with UCI identification system.

• ETRI Journal
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• v.46 no.4
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• pp.697-707
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• 2024

Music identification is widely regarded as a solved problem for music searching in quiet environments, but its performance tends to degrade in TV broadcast audio owing to the presence of dialogue or sound effects. In addition, constructing an accurate dataset for measuring the performance of background music monitoring in TV broadcast audio is challenging. We propose a framework for monitoring background music by automatic identification and introduce a background music cue sheet. The framework comprises three main components: music identification, music-speech separation, and music detection. In addition, we introduce the Cue-K-Drama dataset, which includes reference songs, audio tracks from 60 episodes of five Korean TV drama series, and corresponding cue sheets that provide the start and end timestamps of background music. Experimental results on the constructed and existing datasets demonstrate that the proposed framework, which incorporates music identification with music-speech separation and music detection, effectively enhances TV broadcast audio monitoring.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.151-168
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• 2014

UCI (Universal Content Identifier) as a national digital content identification system for identifying digital content and ICN (Integrated Copyright Number) for copyright management are operated by Korea copyright commission. However, They are not interoperable with international standard identification system such as ISRC (International Standard Recording Code), ISWC (International Standard Works Code), and ISAN (International Standard Audiovisual Number) due to lack of linkage system. Hence, extra works with international standard identification system are needed for international market entry and integrated management of statistical information including content settlement in international market is impossible. In this paper, the domestic/international identification systems are surveyed, and by metadata analysis of identification systems, linkage method with UCI/ICN is proposed. And also by developing the prototype model, research direction to UCI/ICN with international standard identification system is proposed.

• International Journal of Contents
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• v.6 no.3
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• pp.5-9
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• 2010

To manage large database system with video, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for frame-wise user query or video content query, whereas a few video identification algorithms have been proposed for video sequence query. In this paper, we propose an effective video identification algorithm for video sequence query that employs the Cauchy function of histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences with a low computational load, we make use of the key frames extracted by the cumulative Cauchy function and compare the set of key frames using the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed algorithm for video identification yields remarkably higher performance than conventional algorithms such as Euclidean metric, and directed divergence methods.

• ETRI Journal
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• v.38 no.1
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• pp.174-184
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• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.179-193
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• 2004

Introduction of domestic digital content identification system mean to building district identification by supplying international identification system and interoperability that reflect domestic special state than accept it as it is. This study presented an policy direction for the domestic digital content identification system by the results that analyzed of the identification systems that were commonly used internationally. An identification system is composed to a registration authority, registration agencies, registrants. There should be defined their roles and set up their cooperative system to be able to bring efficiency into more.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.385-396
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• 2011

The purpose of this study was to investigate contents identification and brand community identification on the brand community. Analysis was performed for the empirical study where important variables of this framework included attractiveness, similarity, intimacy, information quality, contents identification, and community identification, loyalty. I collected the 184 data through survey and analyzed them. The data were recorded and analyzed using the SPSS 14.0 and LSREL 8.30. The brief findings of the study were as below: Given the finding of the study, users who have contents identification directly don't affect on purchase loyalty. Therefore, company intensifies users' visiting community. Users who consistently visit community have purchase loyalty. Existing studies on online brand community is a study for the identification. This study identified the dimensions of the content attribute of the content identification and brand community identification were examined by questionnaires. Accordingly, the company operating the brand community to provide more useful suggestions.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.599-608
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• 2007

This study was conducted to establish an individual identification system in Hanwoo cattle. Samples of 33 Hanwoo individuals from Korean elite sire families were used. Thirteen major microsatellite markers were selected from alleles amplified, their frequencies, H(Heterozygosity) and PIC(Polymorphism Information Content) with Hardy-Weinberg equilibrium. Next, in order to evaluate the power of the markers selected on the individual animal identification, MP(Match probability) and R(Relatedness coefficient) with the percentage of animal incorrectly identified were computed. Finally nine microsatellite markers were selected and discussed.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.195-210
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• 2003

With the rapid development of information technology and internet in these days, resources of knowledge information have been digitalized and distributed on the internet, However, the location of digital content and a change of content have generated problems for users access and services. In line with this regard, the research on the identification of digital content utilizing standardized identification system and distribution system is necessary. This study intends to contribute to the implementation of information system based on standard digital identifier for the effective management and safe distribution of digital contents. This study first tries to survey SDI outline, practical application case and distributed business model and to analyze information distribution status Finally, this study tries to draw up a plan for the establishment of KISTI's SDI. content identification system, content distribution system.