• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.11-24
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• 2019

The tendency of buyers of web information is changing from the cost-effectiveness to the cost-satisfaction. There is such tendency in the recommendation of multimedia contents, some of which are folksonomy-based recommendation services using mood. However, there is a problem that they does not consider synonyms. In order to solve this problem, some studies have solved the problem by defining 12 moods of Thayer model as AV values (Arousal and Valence), but the recommendation performance is lower than that of a keyword-based method at the recall level 0.1. In this paper, we propose a method based on using mood vector of multimedia contents. The method can solve the synonym problem while maintaining the same performance as the keyword-based method even at the recall level 0.1. Also, for performance analysis, we compare the proposed method with an existing method based on AV value and a keyword-based method. The result shows that the proposed method outperform the existing methods.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.301-306
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• 2017

This study is intended to analyze colors felt in TV commercials among video contents, to provide basic resources of color plan that can be applied to production of contents and to help acceptors to change their mood and to lower depression levels. Many studies have revealed the obvious correlation between depression and suicide, so the World Health Organization(WHO) recommends the importance of media by recognizing public that depression is a serious risk factor that leads to suicides and by asserting the necessity of establishing social environment for active treatment. Contents production companies have social and cultural responsibility to convey correct information and to make acceptors have positive emotions. If the result of colors that emotionally healthy people feel through this study is used for production of video contents, it will be helpful to lower the depression scale and to prevent and treat depression by providing visual comfort. In addition, it is expected to be used as an important basic resource for not only production of video contents but also color plan of industrial fields.

• Journal of IKEEE
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• v.14 no.4
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• pp.305-311
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• 2010

Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

• Journal of Korea Multimedia Society
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• v.18 no.8
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• pp.988-995
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• 2015

In 2013, Academy Award for Best Animated Short Film was granted to Walt Disney's short animation, (2012). With various aspects of its excellence, I focus on the very effective use of digital lightings and underscores for storytelling as its success factors. In this respect, this paper aims at analyzing the roles of the visual factors, especially tone, contrast, etc. created by lightings, and audio factors, especially underscores, in the film's story development. I find that can be characterized by the well-built story structure with distinct three acts. The main stream of the story is expressed with the overall mood that is created by the fine adjustments of brightness of the main light, and contrast. And the direction and the intensity of the lighting successfully describe the emotions of the characters in each scene. In addition, I find that properly chosen and positioned underscores make the development of the story more dynamic and more harmonized.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.59-66
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• 2015

To date, contents' usability of most multimedia devices has been focused on developer not on user, which made difficult in solving the problems or fulfilling the needs while people using real system. Although user-centered UX and UI researches have been studied and have resulted in innovation in some part, it does not show great effect on usability as it is not easy to interpret human emotions and needs and to apply those to system. Usability is the matter on how deeply smart devices can interpret and analyze human mind not on how much functions and technologies are improved. This study aims to help with usability improvement based on user when people use smart devices in multimedia environment. We studied the interaction between human and contents by analyzing the effect of human emotions and personalities on preference and consumption of contents' type. This study was done by assuming that proper analysis on human emotions may increase user satisfaction on multimedia environment. We analyzed contents preference by gender and emotion. The results showed that there is significant relationship between 'Happy' emotion and 'Comedy Program' preference and men are more prefer it than women. However, it does not reveal any significant relationship between 'Sad' emotion and contents preferences but women are slightly more prefer 'Comedy Program' than men. This result supports the Zillmann's 'mood based management', which suggests that the needs for pleasant contents are revealed to relieve sadness when people are in a sad mood. In addition, our finding corresponds with Oliver's insistence on meeting all four factors, insight, meaningfulness, understanding and reflection, rather than just pleasure for more satisfaction. This study focused on temporary emotional factors and contents and additionally on effect of users' emotion, personality and preference on type of contents consumption. This relationship between emotions and contents study would suggest the better direction for developing smart devices with great contents usability and user satisfaction in the future.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.307-316
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• 2016

A user usually gets the same suggesting results as everyone else in most of the multimedia social services, nowadays. To address the challenging problem of personalization in the social network, we propose a method which exploits user's activities, user's moods, and user's friend relationships from the social network to build a decision-making system. Depending on a current state of the user's mood, this system infers the most appropriated video for the user. In the system, the user evaluates a set of the given recommendation methods which extract from the user's database social network and assigns a vague value to each method by a weight. Then, we find the fuzzy collection solution for the system and classify the set of methods into subsets, and order the subsets based on its local dominance to choose the best appropriate method. Finally, we conduct an experiment using the YouTube API with a lot of video types. The experiment result shows that the channel recommendation system appropriately affords the user's character, it is more satisfying than the current YouTube based on an evaluation of several users.