• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.85-96
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• 2022

The purpose of this study was to analyze the effect of service factors of used book transactions, which are becoming a major service in online bookstores, on customer satisfaction and the effect of customer satisfaction on reuse intention. 235 samples were collected through a survey for users of used book transaction services in their 20s or older, and 205 surveys were adopted through the refining process. Hypotheses were verified through factor analysis, reliability analysis, and structural model analysis using SPSS22.0 and AMOS22.0 statistical programs. Some factors were supported between service factors and customer satisfaction, and customer satisfaction had a significant effect on reuse intention, and moderating effects according to the preferred genre of reading were founded. More differentiated services should be considered according to the customer's preferred genre, as the services of online bookstores are becoming more standardized, customers do not feel differentiated.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.557-561
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• 2021

A meatadata has become an essential element in order to recommend video content to users. However, it is passively generated by video content providers. In the paper, a method for automatically generating metadata was studied in the existing manual metadata input method. In addition to the method of extracting emotion tags in the previous study, a study was conducted on a method for automatically generating metadata for genre and country of production through movie audio. The genre was extracted from the audio spectrogram using the ResNet34 artificial neural network model, a transfer learning model, and the language of the speaker in the movie was detected through speech recognition. Through this, it was possible to confirm the possibility of automatically generating metadata through artificial intelligence.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.238-252
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• 2009

Due to the rapid increase of available contents via the convergence of broadcasting and internet, the efficient access to personally preferred contents has become an important issue. In this paper, for recommendation scheme for TV programs using a collaborative filtering technique is studied. For recommendation of user preferred TV programs, our proposed recommendation scheme consists of offline and online computation. About offline computation, we propose reasoning implicitly each user's preference in TV programs in terms of program contents, genres and channels, and propose clustering users based on each user's preferences in terms of genres and channels by dynamic fuzzy clustering method. After an active user logs in, to recommend TV programs to the user with high accuracy, the online computation includes pulling similar users to an active user by similarity measure based on the standard preference list of active user and filtering-out of the watched TV programs of the similar users, which do not exist in EPG and ranking of the remaining TV programs by proposed rank model. Especially, in this paper, the BM (Best Match) algorithm is extended to make the recommended TV programs be ranked by taking into account user's preferences. The experimental results show that the proposed scheme with the extended BM model yields 62.1% of prediction accuracy in top five recommendations for the TV watching history of 2,441 people.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.173-199
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• 2021

In this study, in order to understand the characteristics of the users' information needs for each public library unit, the user needs were analyzed based on the various attribute information of the books loaned to 11 public libraries in 8 districts in Seoul. As a result, the prominent book use patterns of the libraries were revealed, specifically related to the target user groups, purpose/motivation, interests/preferences, book genre, and subject. In addition, there was a preference for authors, and a difference in the role of the preferred authors in each library was also revealed. The results of this study will help to provide guidelines for the development of differentiated collections and service programs based on user needs.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.547-554
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• 2006

우리 춤은 우리 고유의 정서를 담고 있는 종합예술이므로 우리 춤을 분석하고 이해하는 것은 큰 의미가 있다. 본 논문에서는 기존의 춤 동작의 정량적인 분석을 통한 감정인식 기술을 이용하여 우리 춤에 내포된 감정 패턴의 변화를 살펴본다. 먼저 한국 전통춤으로부터 무용전문가들의 정성적 분석에 기반하여 추출된 우리 춤사위를 정해진 각 감정별로 재구성하여 창작하고 창작된 우리 춤을 무용전문가가 시연한다. 이를 카메라를 이용하여 획득하고, 영상처리를 통해서 시연자의 실루엣을 뽑아낸 후, 정량적 특징량들을 추출한다. 이어 신경회로망을 이용하여 각 감정별 춤사위를 학습 시킨 후, 임의의 춤사위에 내포된 감정을 인식 한다. 본 논문에서는 정면, 좌, 우 세 시점에서 획득된 다시점 영상을 이용하여 학습시킴으로써 보다 안정적으로 동작하는 인식 시스템을 제안한다. 그리고, 시스템에 의해 인식된 감정 패턴과 변화의 정성적 의미를 이해하기 위해 무용전문가들에 의해 정립된 정성적 분석 결과와 비교, 분석한다. 이는 정성적인 분석에만 국한되던 우리 춤의 특성에 대한 이해를 객관적이고 정량화된 분석을 통한 이해의 차원으로 확장시키는 것으로, 우리 춤의 특성을 새롭게 정의하는 계기를 마련할 수 있다. 다양한 장르의 한국 전통춤 가운데 우리 춤을 대표할 수 있는 춤사위를 선정하고, 정성적/정량적으로 분석함으로써 우리 춤의 특성을 이해하기 위한 체계적인 틀을 제공하고자 한다.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.279-286
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• 2006

Classification method used in this paper is applied for the first time to Korean traditional music. Among the frequency distribution vectors, average peak value is suggested and proved effective comparing to previous classification success rate. Mean, variance, spectral centroid, average peak value and ZCR are used to classify Korean traditional musical instruments. To achieve Korean traditional instruments automatic classification, Spectral analysis is used. For the spectral domain, Various functions are introduced to extract features from the data files. k-NN classification algorithm is applied to experiments. Taegum, gayagum and violin are classified in accuracy of 94.44% which is higher than previous success rate 87%.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.

• Journal of Broadcast Engineering
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• v.11 no.3 s.32
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• pp.311-319
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• 2006

Platform operators adopted ATSC standard send only their own channel program schedule information, so in order for the viewer to see other channel information, they have to tune the channel to the other. This issue arises from the operators' lack of bandwidth and the business interest conflicts between the platform operators. This paper guides how ATSC standard could be used within Xlet based application to display other channel information through the ISG (Integrated Scheduling Guide) technology via interactive return channel services. Its own channel information can be displayed by using on-air PSIP (Program and System Information Protocol) data.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.442-449
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• 2006

탈 장르화와 영상의 다양화로 예술에서의 표현의 한계는 극대화 되고 있으며, 디지털 매체를 통한 인터랙션 역시 디지털 아트에서의 보편적인 표현 방법으로 전환 되었다. 예술에서의 상호작용은 보여주는 것에서 참여하는 것으로의 전환을 꿰 하고 있고, 디지털을 기반으로 한 다매체, 다중화가 이를 뒷받침 한다. 상호작용을 위한 디지털 아트 작품을 위해서는 센서를 이용한 표현방법들이 있으나, 기타의 센서도구를 사용치 않고, 단지 카메라로부터 입력된 신호만을 기반으로 영상과 관객의 상호작용을 끌어 낼 수 있다. 이를 위해서는 모션트레킹을 위한 알고리즘을 응용함으로써 사물의 밝기 값에 충족한 데이터를 만들어 낼 수 있고 그에 해당하는 밝기의 변환 값을 이용해 미세한 사물의 변화를 감지 할 수 있는 것이다. 이런 일련의 영상작업을 위해서는 사물의 움직임과 반복성을 얼마만큼 인지하고 감지 해내느냐고 관건인데, 다시 말해 한번 측정한 움직임이 있는 사물의 데이터도 프로그램상에서 계속하여 인지가 되어야 하고, 그 데이터 값을 영상으로 반환하여야 하는데, 이는 영상의 지속적인 변화를 가져 올 수 있다는 걸 의미한다. 따라서 본 논문에서는 모션 트래킹의 기본 알고리즘을 제시하고 영상작품과 인턱래션작품의 변환를 위해 사용된, 센서 대체도구인 웹 캠의 데이터 즉, 색상 값과 밝기 값을 적절하게 활용함으로써 표현의 다양성을 이끌어 내고 디지털 인터랙티브 작품으로써의 제작을 꾀하고자 한다.

• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.225-241
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• 2009

This paper presents an authorship attribution study in Korean conducted on a corpus of newspaper column texts. Based on the data set consisting of a total of 160 columns written by four columnists of Chosun Daily, the approach utilizes relative frequencies of various lexical units in Korean such as fully inflected words, morphemes, syllables and their bigrams in an attempt to establish authorship of a blind text selected from the set. Among these various lexical units, "the morpheme" is found to be most effective in predicting who among the four potential candidates authored a text, reporting accuracies of over 93%. The results indicate that quantitative and statistical techniques in authorship attribution and computational stylistics can be successfully applied to Korean texts.