• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.216-219
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• 2011

인터넷 기술이 빠르게 발전하고 변화하여 현재는 많은 수의 컨텐츠와 프로그램 채널이 IP 네트워크를 통해 제공되면서 컨텐츠 서비스 사업자들은 좀 더 향상된 추천시스템이 필요하게 되었다. 그리고 사용자 참여중심의 인터넷 환경인 Web 2.0 시대가 도래하면서 사용자가 직접 생성한 정보들을 활용하는 다양한 연구가 진행되고 있다. 본 논문에서는 타겟 아이템에 대해 인터넷 상에 수많은 사용자들이 생성한 정보들을 ConceptNet을 활용하여 감정벡터를 추출하고 장르별로 분류하는 방법을 결합한 새로운 형태의 영화 추천시스템을 제안한다. 공개용 영화 데이터인 MovieLens 데이터 셋을 이용하여 실험하였고 성능평가는 RMSE 방법과 다양한 추천평가방법으로 기존 협업 필터링 추천시스템과 비교하였으며 실험 결과 기존방식보다 향상된 성능을 보였다.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.31-32
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• 2018

본 논문은 연대기적 흐름에 따른 영화 이론의 발전 양상을 통해 영화의 분석 방법과 관점을 어떻게 분류해야 하는지 제시하고자 한다. 영화는 고전과 현대를 명확히 나누기는 모호하지만 제 2차 세계대전을 기준으로 전과 후를 분류할 수 있다. 영화 초기에는 장르가 다양하지 않았지만 현대로 가면서 점차 고전적 내러티브에서 벗어나 새로운 장르와 형식을 추구했기 때문에 영화와 그 이론 또한 영역이 확장되었다. 이러한 영화의 유형은 고전 영화를 근간으로 발전하여 실험영화로서의 다양한 형태와 이론을 제시하게 되었다. 따라서 영화 이론의 흐름이 어떤 식으로 발전되었으며 그것이 현대 영화를 분석할 때에 어떻게 접근해야 하는가에 대한 관점을 고찰한다.

• The Korean Publising Journal, Monthly
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• s.249
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• pp.11-11
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• 1999

이제까지 문화관련서들은 각 장르의 예술작품 비평서와 에세이가 주류였다. 이들을 전문예술 영역으로 분류한다면 이제는 삶의 양식과 기반의, 보다 포괄적인 삶의 조건으로 문화를 파악하려는 시도가 필요할 때다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.1-7
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• 2009

An approach for the classification of music genres using a Fuzzy c-Means(FcM) with divergence-based kernel is proposed and presented in this paper. The proposed model utilizes the mean and covariance information of feature vectors extracted from music data and modelled by Gaussian Probability Density Function (GPDF). Furthermore, since the classifier utilizes a kernel method that can convert a complicated nonlinear classification boundary to a simpler linear one, he classifier can improve its classification accuracy over conventional algorithms. Experiments and results on collected music data sets demonstrate hat the proposed classification scheme outperforms conventional algorithms including FcM and SOM 17.73%-21.84% on average in terms of classification accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.884-889
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• 2010

Recently, a music genre classification has been studied. However, experts use different criteria to classify each of these classifications is difficult to derive accurate results. In addition, when the emergence of a new genre of music genre is a newly re-defined. Music as a genre rather than to separate search should be classified as emotional words. In this paper, the feelings of people on the basis of brightness and darkness tries to categorize music. The proposed classification system by applying VCM(Variance Considered Machines) is the contrast of the music. In this paper, we are using three kinds of musical characteristics. Based on surveys made throughout the learning, based on musical attributes(beat, timbre, note) was used to study in the VCM. VCM is classified by the trained compared with the results of the survey were analyzed. Note extraction using the MATLAB, sampled at regular intervals to share music via the FFT frequency analysis by the sector average is defined as representing the element extracted note by quantifying the height of the entire distribution was identified. Cumulative frequency distribution in the entire frequency rage, using the difference in Timbre and were quantified. VCM applied to these three characteristics with the experimental results by comparing the survey results to see the contrast of the music with a probability of 95.4% confirmed that the two separate.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.238-244
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• 2013

For musical genre classification, various types of feature vectors are utilized. Mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), and octave-based spectral contrast (OSC) are widely used as short-term features, and their long-term variations are also utilized. In this paper, OSC features are extracted not only in the single-octave band domain, but also in the multiple-octave band one to capture the correlation between octave bands. As a baseline system, we select the genre classification system that won the fourth place in the 2012 music information retrieval evaluation exchange (MIREX) contest. By applying the OSC features based on multiple-octave bands, we obtain the better classification accuracy by 0.40% and 3.15% for the GTZAN and Ballroom databases, respectively.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.5-22
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• 2006

A cultural classification and a culture contents industrial classification are the basic tools for cultural policies, cultural supporting, cultural statistics, and evaluations and there is a cyclic processes among them. This study finds out the varieties and short time changes of cultural categorization in laws, statistics, indexes, evaluations, research reports. As a result, colon style new cultural classification is suggested which used networks, media, genre, and cultural comparts as principles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4762-4768
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• 2013

This paper investigated the impacts of theme, genre, and existence of originals on the number of visitors of children performance. Especially, we focused on the interaction effect of school periods with these variables. Using 954 performance data between 2010-2011 at Fantasia Theater run by Bucheon Culture Foundation, we found that entertaining performance, musical performance, and performance with existing originals had more visitors than others. Also, these impacts strongly existed during school periods. In result, this study found that school period should be considered seriously for the success of children performance.

• The Journal of the Korea Contents Association
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• v.13 no.10
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• pp.160-169
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• 2013

The materials used in the title sequence connotes a style & a content of film comprehensively. Therefore, the effect of emotional expression can be changed according to what materials are selected. Thus, the materials of which 42 title sequences are collected for the last 10 years are classified, and the category of materiality & material degree are defined with the semiotic rectangle. To investigate intensity of the material degree, the survey was done. As a result of the survey, the intensity was classified into 3 levels of material degree. The category of materiality used according to the genre of film was analyzed. As a result of the analysis, the materiality was selected according to the content regardless of genre, but there's any difference in the material degree. The intense material degree was used in a thriller and an SF mystery genre, and the medium one was used in the general genre, but, above all, drama and action genre. The weak one was used in a variety of genre, but specifically horror, SF mystery genre. It is significant that this study suggested the expression method in accordance with selection of materials in producing a title sequence to visualize film symbolically.