• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.693-694
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• 2014

This short paper briefly describes the proposed music recommendation method that provides suitable music pieces to a listener depending on both listeners' ratings and content of music pieces. The proposed method consists of two methods. First, listeners' ratings prediction method is a combination the traditional user-based and item-based collaborative filtering methods. Second, genre classification method is a combination of feature extraction and classification procedures. The feature extraction step obtains audio signal information and stores it in data structure, while the second one classifies the music pieces into various genres using decision tree algorithm.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.89-98
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• 2007

For browsing, searching, and manipulating video documents, an indexing technique to describe video contents is required. Until now, the indexing process is mostly carried out by specialists who manually assign a few keywords to the video contents and thereby this work becomes an expensive and time consuming task. Therefore, automatic classification of video content is necessary. We propose a fully automatic and computationally efficient method for analysis and summarization of spots news video for 5 spots news video such as soccer, golf, baseball, basketball and volleyball. First of all, spots news videos are classified as anchor-person Shots, and the other shots are classified as news reports shots. Shot classification is based on image preprocessing and color features of the anchor-person shots. We then use the dominant color of the field and motion features for analysis of sports shots, Finally, sports shots are classified into five genre type. We achieved an overall average classification accuracy of 75% on sports news videos with 241 scenes. Therefore, the proposed method can be further used to search news video for individual sports news and sports highlights.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1527-1530
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• 2002

Video summary is one of the tools which can provide the fast and effective browsing fur a lengthy video. Video summary consists of many key-frames that could be defined differently depending on the video genre it belongs to. Consequently, the video summary constructed by the uniform manner might lead into inadequate result. Therefore, identifying the video genre is the important first step in generating the meaningful video summary. We propose a new method that can classify the genre of the video data in MPEG compressed bit-stream domain. Since the proposed method operates directly on the com- pressed bit-stream without decoding the frame, it has merits such as simple calculation and short processing time. In the proposed method, only the visual information is utilized through the spatial-temporal analysis to classify the video genre. Experiments are done for 6 genres of video: Cartoon, Commercial, Music Video, News, Sports, and Talk Show. Experimental result shows more than 90% of accuracy in genre classification for the well-structured video data such as Talk Show and Sports.

• Archives of design research
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• v.16 no.3
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• pp.351-360
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• 2003

The concept of genre used to be applied to classify the fine arts also can investigate various way of communication system and classification. The structuring element of genre was identified by form and contents in that field. But the classification of the web, which is new communication tool, was made by defining the purpose of the web. In this paper the genre system, which consists of form, contents, and function, is applied to classify the web so that we offer tile opportunity to identify dearer characteristics of it. In order to investigate the genre elements in the communication process the structure of the semiotic triad after Charles S. Peirce was adapted, which was labeled as representamen, object, and interpretant. The representamen substitutes for the web function, the object does for the form of the web, and the representamen does for the web contents. According to the Peirce's the representamen identify the object but on the other hand it is identified by the interpretant. Logical structure of the fact that form of the web is identified by its function, and the function is identified by the contents is proved by following the theory. Therefore, the concept of web genre is supported by the element of genre having a logical structure activating in the communication process. We suggest that in recent complicated communication circumstance the genre concept should be adapted to implement the effective web communication design.

• Journal of Korea Game Society
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• v.8 no.3
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• pp.3-14
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• 2008

Classifying digital games' genres is quite ambiguous work, as they have been using other media's genre classification such as film genre. Therefore this paper tries to propose a new way of classifying genres of digital games. There are two kinds of approaches to digital games genres: one is based on gamers' activities and the other is on game text. The former turned out to be limitative because the meanings of gamers' activities are sometimes overlapped and this overlapping causes lack of objectivity in deciding which activity belongs to which genre. On the other hand, the latter is comparatively clear and accurate as it is based on what a game text provides. After all. a new classification of digital games based on game text makes total of 7 digital game types, which are Physical obstacles, Mainly Physical & partially intellectual obstacles, Intellectual obstacles, Mainly intellectual & partially physical obstacles, Self-supporting games, Confronting games, Ranking games, and each type has its own convention and characteristics.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1119-1125
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• 2017

Genres and actions of stories can be used to classify stories, and used effectively as well for visualizing story properties. This paper proposes a Genre-Action coordinate system for visualizing story property data in 2-dimension that has similarities between the genre and action items along the axes, i.e. a property of spatial continuum. With the proposed Genre-Action coordinate system we found that the genre and action items in the axes are arranged according to their similarities and we were able to achieve a spatially meaningful visualization of story properties where the related data form clusters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.121-127
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• 2009

The Multistage Feature-based Classification Model(MFCM) is proposed in this paper. MFCM does not use whole feature vectors extracted from the original data at once to classify each data, but use only groups related to each feature vector to classify separately. In the training stage, the contribution rate calculated from each feature vector group is drew throughout the accuracy of each feature vector group and then, in the testing stage, the final classification result is obtained by applying weights corresponding to the contribution rate of each feature vector group. In this paper, the proposed MFCM algorithm is applied to the problem of music genre classification. The results demonstrate that the proposed MFCM outperforms conventional algorithms by 7% - 13% on average in terms of classification accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.36-41
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• 2010

An advanced form of Multistage Feature-based Classification Model(AMFCM), called AMFCM, is proposed in this paper. AMFCM like MFCM does not use the concatenated form of available feature vectors extracted from original data to classify each data, but uses only groups related to each feature vector to classify separately. The prpposed AMFCM improves the contribution rate used in MFCM and proposes a confusion table for each local classifier using a specific feature vector group. The confusion table for each local classifier contains accuracy information of each local classifier on each class of data. The proposed AMFCM is applied to the problem of music genre classification on a set of music data. The results demonstrate that the proposed AMFCM outperforms MFCM by 8% - 15% on average in terms of classification accuracy depending on the grouping algorithms used for local classifiers and the number of clusters.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.145-151
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• 2011

This study assumed the competitive structure based on genre classification for Korean online game contents market, and carried out the analysis on the degree and characteristics of the competition that appear differently in each sub market classified according to the genre. First, to analyze the market power of the rank 1 and 2 game contents in each genre, using the play time share ratio and standard deviation statistics values in the genre, ANOVA analysis and Cluster analysis were carried out for each genre. According to ANOVA analysis result, in the rank 1 game share ratio in each genre, there was a relationship of 'FPS/Racing > RST/Sports > Poker > Go-stop > RPG > Arcade > Board', and in the play time total share ratio of rank 1 and 2 games, the relationship of 'RTS > FPS/Racing > Sports > RPG > Go-stop > Poker > Arcade > Board' was verified. And in Cluster analysis, the groups of the genres with the degree of market power tendency and the variability at similar level were classified and stated.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.413-422
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• 2012

Many researchers have been studied to reveal human natural language to let machine understand its meaning by text based, page rank based or more. Particularly, it has been considered that URL and HTML Tag information in web documents are attracting people' attention again to analyze huge amount of web document automatically. In this paper, we propose a STW (Semantic Term Weight) approach based on syntactic and linguistic structure of web documents in order to classify what genres are. For the evaluation, we analyzed more than 1,000 documents from 20-Genre-collection corpus for training the documents based on SVM algorithm. Afterwards, we tested KI-04 corpus to evaluate performance of our proposed method. This paper measured their accuracy by classifying them into an experiment using STW and one without u sing STW. As the results, the proposed STW based approach showed approximately 10.2% which Is higher than one without use of STW.