• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.41-44
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• 2011

본 연구는 현재 사용자가 청취한 음악과 청취한 순서를 기반으로 다음에 사용할 아이템을 추천하는 문제를 다룬다. 우리가 제시하는 모델은 아이템 사용 로그를 기반으로 하며, 정보검색에서 많이 사용하는 N-gram모델을 사용하여 아이템의 순서열을 추출한 후 다음에 올 확률이 높은 아이템을 학습한다. 그리고 사용자가 현재 선택한 아이템의 순서열을 기반으로 다음에 가장 들을 확률이 높은 아이템을 추천한다. 또 실 세계 데이터를 기반으로 실험하여 협업적 필터링 방식과 성능을 비교한다.

• The Journal of the Acoustical Society of Korea
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• v.36 no.2
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• pp.144-150
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• 2017

Musical genre is indispensible in constructing music information retrieval system, such as music search and classification. In general, the spectral characteristics of a music signal are obtained based on a subband decomposition to represent the relative distribution of the harmonic and the non-harmonic components. In this paper, we investigate the subband decomposition parameters in extracting features, which improves musical genre classification accuracy. In addition, the linear projection methods are studied to reduce the resulting feature dimension. Experiments on the widely used music datasets confirmed that the subband decomposition finer than the widely-adopted octave scale is conducive in improving genre-classification accuracy and showed that the feature-dimension reduction is effective reducing a classifier's computational complexity.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.760-765
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• 2008

The purpose of this paper is to propose a powerful alternative in designing knowledge portals using Topic Maps(TM). All information is processing for one topic, about each topics define to association and composite flow of information. and all topics about add occurrence to use in the OpenAPI. Also represent to UI of graphic for intuitional representation, and using JavaScript for Cross-Browsing. so that not using XTM of a standard Topic Maps(TM) and using JSON for a simple represent to data. The results made for intuitional process UI and extensive limits to display for new information before until now musician search system. In future positive to musician search for music.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.151-158
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• 2006

In this paper, we proposed a new audio fingerprint extraction method, based on Philips' music retrieval algorithm, which uses the energy difference of neighboring filter-bank and probabilistic characteristics of music. Since Philips method uses too many filter-banks in limited frequency band, it may cause audio fingerprints to be highly sensitive to additive noises and to have too high correlation between neighboring bands. The proposed method improves robustness to noises by reducing the number of filter-banks while it maintains the discriminative power by representing the energy difference of bands with 2 bits where the quantization levels are determined by probabilistic characteristics. The correlation which exists among 4 different levels in 2 bits is not only utilized in similarity measurement. but also in efficient reduction of searching area. Experiments show that the proposed method is not only more robust to various environmental noises (street, department, car, office, and restaurant), but also takes less time for database search than Philips in the case where music is highly degraded.

• Journal of Korean Library and Information Science Society
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• v.38 no.3
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• pp.223-246
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• 2007

This study examines the retrieval efficiency of the FRBR-based bibliographic retrieval system. To do this, we built two experimental retrieval systems(a FRBR-based system constructed through FRBRizing algorithms and an OPAC-based retrieval system) using 387 music materials coded in a KORMARC format. Next, we set up six hypotheses and compared these two systems in terms of recall, precision, and retrieval time using 28 participants and a questionnaire with 12 queries. The results show that the average recall value of the FRBR-based system Is higher than that of the OPAC system regardless of query types and the average precision and retrieval time values of manifestation queries of the OPAC system is more efficient that those of the FRBR-based system. This study results can be used to customize digital library interfaces as well as to improve the retrieval efficiency of the bibliographic retrieval system.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.223-254
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• 2019

The research on the archiving performing arts has recently been conducted on various aspects in Korea, but there has been no research or attempts to build a digital archive that can systematically identify the information on classical music performances in one place and get the past performance information. In this study, we proposed a participatory archive portal for providing, preserving and servicing information on all classical music performances, and tried to design the functions based on the requirements of the performance archive portal identified in previous research. We identified and proposed functional requirements of the portal, reorganized the characteristics of classical music performance information, and designed metadata elements. Then we presented the design and implementation direction of search and facet navigation, as well as user participation and communication functions. Lastly, we developed a prototype that implemented the requirements of the interface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.461-468
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• 2000

Amounts of audio data used in several computer application have necessitated the development of audio database systems with newer features such as content-based queries and similarity searches to manage and use such data. Fast and accurate retrievals for content-based queries are crucial for such systems to be useful. Efficient content-based indexing and similarity searching schemes are keys to providing fast and relevant data retrievals. This paper present a method for indexing of Korean Traditional Music audio data based on wavelets. Also this paper present possibility of wavelet based audio indexing.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.406-411
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• 2008

인터넷을 비롯한 통신 네트워크의 발전으로 개개인의 콘텐츠 수요가 증가함에 따라 다양한 콘텐츠 욕구를 충족시키기 위한 추천 시스템이 대두되고 있으며, 이러한 추천 시스템의 기반 기술로써 내용 기반 검색 기술의 필요가 증가하고 있다. 본 논문에서는 대표적인 멀티미디어 콘텐츠의 하나인 음악의 무드를 내용 기반으로 분류하기 위해, 음악 비트 검출에 기반한 프레임화를 적용하였으며, 스펙트럼의 고조파를 좀더 강조하기 위한 HDS(Harmonic Distribution Spectrum)을 제안하였다. 또한 다양한 차원 감쇄 기법과 분류기를 이용한 실험을 통해 무드 분류 시스템의 성능 비교를 진행하였다.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.5-30
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• 2002

In this paper, classification feature is selected with focus of musical content, note sequences pattern, and measures similarity between note sequences followed by constructing clusters by similar note sequences, which is easier for users to search by showing the similar note sequences with the search result in the CBMR system. Experimental document was $\ulcorner$A Dictionary of Musical Themes$\lrcorner$, the index of theme bar focused on classical music and obtained kern-type file. Humdrum Toolkit version 1.0 was used as note sequences treat tool. The hierarchical clustering method is by stages focused on four-type similarity matrices by whether the note sequences segmentation or not and where the starting point is. For the measurement of the result, WACS standard is used in the case of being manual classification and in the case of the note sequences starling from any point in the note sequences, there is used common feature pattern distribution in the cluster obtained from the clustering result. According to the result, clustering with segmented feature unconnected with the starting point Is higher with distinct difference compared with clustering with non-segmented feature.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.479-487
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• 2016

People can listen to almost every type of music by music streaming services without possessing music. Ironically it is difficult to choose what to listen to. A music recommendation system helps people in making a choice. However, existing recommendation systems have high computation complexity and do not consider context information. Emotion is one of the most important context information of music. Lyrics can be easily computed with various language processing techniques and can even be used to extract emotion of music from itself. We suggest a music-level similarity evaluation method using emotion and structure. Our result shows that it is important to consider semantic information when we evaluate similarity of music.