• Title/Summary/Keyword: 장르 선호도

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Influence of Personality Types on Ttelevision Contents Preference (개인성향과 텔레비전 프로그램 유형 선호도의 관계 연구)

  • Yang, Moon-Hee
    • The Journal of the Korea Contents Association
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    • v.11 no.12
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    • pp.230-240
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    • 2011
  • The personality types has been emphasized as one of the influential factors for the program selection by viewers in the multi-channel and multimedia era. However, there have been few empirical studies on this issue. The current study investigated how the audience personality influence the program preference. Specifically, this study focused on both need for cognition and sensation seeking which are related to the television viewing motivation. To examine the influence of personality on program preference, four types of drama and five types of entertainment programs were used. The results of the web survey showed that viewers personality type seem to have effect on their program preference. Indeed, it appeared that there was positive relationship between need for cognition and sensation seeking. The implications of this study's findings were discussed.

An Analysis of 'One Book's Selected in Twenty Years of 'One Book, One City' Reading Campaigns in the U.S.A. (미국 '한 책, 한 도시' 독서운동 20년과 '한 책'의 분석)

  • Yoon, Cheong-Ok
    • Journal of the Korean Society for Library and Information Science
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    • v.51 no.3
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    • pp.45-64
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    • 2017
  • The purpose of this study is to understand the direction of the community reading campaign in the U.S.A. known as 'One Book, One City' reflected in the books selected for this campaign for the past 20 years in terms of their classification numbers, subject headings, publication dates, and genres. Analyzed are the author and state lists of 'One Book, One City' Reading Promotions Projects available from the website of the LC (Library of Congress) Center for the Books, and bibliographic records of 735 books selected in only one 'One Book' program, accessed from LC OPAC. Major findings include continuing influences of the all-time favorite 'One Book' selections, including To Kill a Mockingbird and the extension of their span of life through The Big Read, preference for the recent publications, importance of P (Literatures and Languages) Class (530 titles, 72.1%) and PS(American Literatures) subclass (307 titles, 57.9%) in the LC Classification Scheme, distribution of books in 43 genres, including domestic fiction, historical fiction, and psychological fiction, etc., the use of 535 unique LC subject headings and much interests in "City and town life" (10 titles) and "World War, 1939-1945" (8 titles), and prominence of subject groups which begin with "African American..." and "Woman..." out of 96 groups of subject headings. It is found that the subjects and focus of the selected books expand from integration, understanding, integrity to human rights, environment, peace, etc. The limitations of this study is that the influence of the selected books and the changes in communities are not properly analyed.

User Preference based Intelligent Program Guide (사용자 선호도 기반 지능형 프로그램 가이드)

  • 류지웅;김문철;남제호;강경옥;김진웅
    • Journal of Broadcast Engineering
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    • v.7 no.2
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    • pp.153-167
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    • 2002
  • With the advent of digital broadcasting, a large number of program channels become available at the user terminals such as set-top-box or PC. Channel navigation and searching become more difficult at TV terminal sides using a conventional device such as a TV remote controller. The MPEG-7 MDS (Multimedia Description Scheme) and TV Anytime set up a standard about how to describe user preferences for genre, channel, actor/actress, keyword, etc. of the TV programs, and how to describe usage history for user's program consumption behaviors and preferences. But they do not describe how to use them. In this paper, we describe an IPG (Intelligent Program Guider) system that provides TV program and channel information based on user preferences and suggest easy access to TV program that user wants. The IPG monitors user's behaviors of interacting to programs and automatically updates the user's preference changes according1y. The IPG utilizes user preferences description scheme specified in both MPEG-7 MDS and TV Anytime metadata specifications.

A Webtoon Recommendation System using Opinion Mining and Collaborate Filtering (오피니언 마이닝과 협업필터링을 이용한 웹툰 추천 시스템)

  • Sim, Dae-Su;Park, Jin-Soo;Park, Doo-Soon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.521-524
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    • 2017
  • 최근 다양한 웹툰 콘텐츠의 증가와 함께 스마트폰 보급률이 높아지면서, 사용자들의 실시간 웹툰 서비스의 이용이 증가하고 있다. 웹툰 콘텐츠의 가치가 갈수록 점점 높아지고 있으며, 각종 영화 애니메이션 게임 등 다양한 콘텐츠 사업에 많은 데이터가 사용되고 있다. 본 논문에서는 기존 웹툰의 리뷰를 오피니언 마이닝기법을 사용하여 각 웹툰의 선호도를 평가하며 나이, 성별, 선호 장르, 선호 웹툰 플랫폼 등과 같은 개인 성향을 통하여 사용자간의 유사도를 측정하는 협업 필터링 방법을 적용해 각각의 사용자들이 보고 싶어하는 웹툰을 자동적으로 추천해주는 웹툰 추천 시스템을 제안한다.

Mirrors that Illuminate Culture: Koreans' Cultural Orientation Reflected in Pop Music Preferences (문화를 비추는 거울: 대중음악 선호에 반영된 한국인의 문화성향을 중심으로)

  • Lee, Inyeong;Park, Hyekyung
    • Korean Journal of Culture and Social Issue
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    • v.26 no.3
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    • pp.221-257
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    • 2020
  • This study examined whether popular music lyrics, the new research topic, reflect changes in Koreans' cultural orientation and whether individuals' cultural orientation is related to the genre of popular music that they prefer. In Study 1, we content analyzed popular music lyrics from 1980 to 2018 to see if Koreans' cultural orientations changed over time. The analysis showed that as the release dates approached the 2010s, the lyrics expressed the ideal attitudes of individualist cultures more frequently than those of collectivist cultures; this suggests that Koreans have gradually become more individualistic over time. In Study 2, we examined the relationships between individuals' cultural orientations, preferences for various genres of popular music, and functions of music. The analysis showed that people with more collectivistic attitudes tended to prefer mid- and low-arousal music, such as Ballads and Rap/Hiphop, while those with less collectivistic attitudes preferred high-arousal music, such as Rock/Metal. This result is partly consistent with the hypothesis that collectivistic people would prefer lower to higher arousal music. In addition, our analysis showed the strongest positive relationship between collectivism and the social function of music; this result can be interpreted as indicating that collectivistic people use music to maintain good interpersonal relationships. This paper concludes by discussing the implications of these findings, the limitations of this study, and directions for further research.

An Analysis of Changes in Korean Online-game Market : Focusing on Azuma Hiroki's Postmodern Consumption Theory (국내 온라인게임시장 변화에 대한 분석 : 아즈마 히로키 포스트모던 소비이론을 중심으로)

  • Kim, Ye-Sol;Jin, Hyun-Joung
    • The Journal of the Korea Contents Association
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    • v.20 no.5
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    • pp.665-680
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    • 2020
  • This study analyzed changes in Korean online-game market from RPG to MOBA and FPS/TPS genre, based on Azuma Hiroki's database consumption theory. After selecting the representative game for each genre: World of Warcraft, League of Legends, and Overwatch, we analyzed the games' story, characters, progress, and simulacre produced by game users. The results of this study confirmed that changes in popular genre in the domestic online-game market proceed from consumers' verging toward database consumption. We also found that Korean game users prefer smaller stories and characters based on database, and that consumers have produced more rigorous simulacre than those in other cultural areas and re-databased it for next consumption. This study is the first to analyze changes in the domestic online-game market and adds a contribution to the literature in terms of incorporating Azuma Hiroki's consumption theory into the domestic game market.

A Research on the Audio Utilization Method for Generating Movie Genre Metadata (영화 장르 메타데이터 생성을 위한 오디오 활용 방법에 대한 연구)

  • Yong, Sung-Jung;Park, Hyo-Gyeong;You, Yeon-Hwi;Moon, Il-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.284-286
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    • 2021
  • With the continuous development of the Internet and digital, platforms are emerging to store large amounts of media data and provide customized services to individuals through online. Companies that provide these services recommend movies that suit their personal tastes to promote media consumption. Each company is doing a lot of research on various algorithms to recommend media that users prefer. Movies are divided into genres such as action, melodrama, horror, and drama, and the film's audio (music, sound effect, voice) is an important production element that makes up the film. In this research, based on movie trailers, we extract audio for each genre, check the commonalities of audio for each genre, distinguish movie genres through supervised learning of artificial intelligence, and propose a utilization method for generating metadata in the future.

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Weighted Markov Model for Recommending Personalized Broadcasting Contents (개인화된 방송 컨텐츠 추천을 위한 가중치 적용 Markov 모델)

  • Park, Sung-Joon;Hong, Jong-Kyu;Kang, Sang-Gil;Kim, Young-Kuk
    • Journal of KIISE:Computing Practices and Letters
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    • v.12 no.5
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    • pp.326-338
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    • 2006
  • In this paper, we propose the weighted Markov model for recommending the users' prefered contents in the environment with considering the users' transition of their content consumption mind according to the kind of contents providing in time. In general, TV viewers have an intention to consume again the preferred contents consumed in recent by them. In order to take into the consideration, we modify the preference transition matrix by providing weights to the consecutively consumed contents for recommending the users' preferred contents. We applied the proposed model to the recommendation of TV viewer's genre preference. The experimental result shows that our method is more efficient than the typical methods.

Pairwise fusion approach to cluster analysis with applications to movie data (영화 데이터를 위한 쌍별 규합 접근방식의 군집화 기법)

  • Kim, Hui Jin;Park, Seyoung
    • The Korean Journal of Applied Statistics
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    • v.35 no.2
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    • pp.265-283
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    • 2022
  • MovieLens data consists of recorded movie evaluations that was often used to measure the evaluation score in the recommendation system research field. In this paper, we provide additional information obtained by clustering user-specific genre preference information through movie evaluation data and movie genre data. Because the number of movie ratings per user is very low compared to the total number of movies, the missing rate in this data is very high. For this reason, there are limitations in applying the existing clustering methods. In this paper, we propose a convex clustering-based method using the pairwise fused penalty motivated by the analysis of MovieLens data. In particular, the proposed clustering method execute missing imputation, and at the same time uses movie evaluation and genre weights for each movie to cluster genre preference information possessed by each individual. We compute the proposed optimization using alternating direction method of multipliers algorithm. It is shown that the proposed clustering method is less sensitive to noise and outliers than the existing method through simulation and MovieLens data application.

Recommender Systems in E-Commerce using Collaborative Filtering (협동적 필터링을 이용한 전자상거래에서의 추천시스템)

  • Kim, Young-Seol;Jang, Su-Hyun;Yoon, Byung-Joo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2000.10a
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    • pp.289-292
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    • 2000
  • 인터넷이 생활의 일부분이 되어감에 따라 인터넷상에서 이루어지는 전자상거래는 빠르게 발전하고 있다. 지금까지의 전자상거래는 고객이 요구하는 제품을 판매하는 단순한 형태였다. 하지만 앞으로의 전자상거래에서는 고객이 선호할 만한 제품을 예상하여 고객에게 해당 제품을 추천해 줌으로서 양질의 서비스를 제공하고 더 많은 이익을 창출 할 수 있는 전자상거래 시스템이 요구되고 있다. 본 논문에서는 전자상거래시스템에서 이용될 수 있는 추천시스템을 개발하기 위하여 추천시스템의 핵심이 되는 사용자간 유사도에 기초한 GroupLens의 협동적 필터링 알고리즘을 실제 Data Set을 통해서 실험하였다. 또한 Data Set을 분석하여 아이템을 대표할 수 있는 장르를 결정하여 전체 학습데이터로부터 대표장르에 속하는 데이터들만을 분리하여 학습데이터로 사용하는 추천시스템을 제안하였고, 실험을 통하여 제안한 추천시스템의 타당성을 보였다.

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