• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.689-691
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• 2011

Due to the rapid development of Information and communication, the technology of multimedia presentation technology is evolving into the service that user can actively, realistically enjoy and play based on user's preference and taste not only for User's passive service. Especially, the industry related the realistic multimedia service that supports targeting Human emotion with the property of Human hearing is expected to be formed of the high value-added premium market. Audio technology is affected on human's emotion and the viewing environment around than video technology. Also the audio technology compared to video technology is a research part that appeals to human emotion and emphasize on psychological aspects. With this viewpoint, the development of intelligent and realistic audio technology needs highly specialty. In this study, "intelligent real-sound presentation technology" that support high quality and realistic audio and the "core technologies" that are composing of this will be introduced.

• Korean Journal of Environment and Ecology
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• v.30 no.3
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• pp.434-442
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• 2016

This study examined differences in the preference of the fest therapy program regarding stress level. Using convenience sampling method, the surveys on the preferred type of forest healing program and social and psychological stress scales was carried out for adult male and female. As a basis of Psycho social Stress Scale (PWI-SF: Psychosocial Well-being Index Short Form), the adult 620 people were classified such as healthy group, potential stress group, high-risk stress group. The data were analyzed by use of SPSS 21.0 program. To see the difference in preferences for forest therapy program between the three groups according to stress levels, it was analyzed using one-way ANOVA. Depending on the stress levels, there were differences in the preferences of forest healing program such as breathing, breathing exercises, walking in the forest, listening to the sound of water flowing, viewing the forest, counseling, consultation and expert coaching, stress-related lectures, communication-related lectures, forest bathing wind bathing sun bathing. High-risk stress group preferred cognitive based program such as counseling, consultation and expert coaching, stress-related lectures, communication-related lectures. Healthy group appeared to prefer highly emotional approach of the program to take advantage of the five senses such as breathing, breathing exercises, walking in the forest, listening to the sound of water flowing, viewing the forest, forest bathing, wind bathing, sun bathing. Noticeable preference difference was not observed in the potential stress group. It is hoped this study will serve as a basis for the development of forest healing program regarding stress level.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.709-721
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• 2006

The traditional broadcasting services over terrestrial, satellite and cable media have been unidirectional mass media regardless of TV viewer's preferences. Recently ich media streaming has become possible via the broadb and networks. Furthermore, since bidirectional communication is possible, personalcasting such as personalized streaming services has been emerging by taking into account the user's preference on content genres, viewing times and actors/actresses etc. Accordingly, personal media becomes an important means for content provision service in addition to the traditional broadcasting service as mass media. In this paper, we introduce a user profile reasoning method for target advertisement which is considered an important application in personalcasting service. The proposed user profile reasoning method predicts an unknown TV viewer's gender and ages by analyzing TV Viewing history data. Based on the estimated user's gender and ages, a target advertisement is provided with TV Anytime metadata. A proposed target advertisement system is developed based on the user profile reasoning and the target advertisement selection method. To show the effectiveness of our proposed methods, we present a plenty of experimental results by using realistic TV viewing history data.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.265-275
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• 2019

The purpose of this study is to validate scale of deteminants for watching Korean traditional music performances to activate the market by procuring and increasing Korean traditional music performance consumers that exhibit generally low preference in the performance market. Accordingly, FGI was conducted on seven employees and professionals in the arts and cultural sector and then open survey results were categorized into eight factors and a total of sixty-five items using the KJ method to find the viewing decision factors per consumer type of Korean traditional music performances. Afterwards, a six-factor and thirty-five items were extracted after conducting an exploratory factor analysis and confirmatory factor analysis was conducted to verify the structural appropriateness, and then the feasibility of the composition of Korean traditional music performance viewing decision factor scale was verified. Results of the analysis showed that first, for general Korean adults making decisions to view Korean traditional music performances, there was positive impact in the order of interest-creating factors, fame and talent factors, emotional and information factors, creativity factors, reasonable price factors, and social relation factors. Second, the general tendency of decision factors to view Korean traditional music performances showed relatively high levels in reasonable price factors and interest-creating factors among the Korean traditional music performance viewing decision factors, while emotional and information factors were found to be relatively low.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.88-97
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• 2013

Collaborative filtering(CF) for the personalized recommendation is a successful and popular method in recommender systems. But the mainly researched and implemented cases focus on dealing with independent items with explicit feedback by users. For the domain of TV program recommendation in VOD service platform, we need to consider the unique characteristic and constraints of the domain. In this paper, we studied on the way to convert the viewing history of each TV program episodes to the TV program preference by considering the series structure of TV program. The former is implicit for personalized preference, but the latter tells quite explicitly about the persistent preference. Collaborative filtering is done by the unit of series while data gathering and final recommendation is done by the unit of episodes. As a result, we modified CF to make it more suitable for the domain of TV program VOD recommendation. Our experimental study shows that it is more precise in performance, yet more compact in calculation compared to the plain CF approaches. It can be combined with other existing CF techniques as an algorithm module.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.9
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• pp.835-840
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• 2008

This paper proposes an enhanced recommendation technique for personalized e-commerce portal analyzing various attitudes of customer. The attitudes are classifies into three types such as "purchasing product", "adding product to shopping cart", and "viewing the product information". We implicitly track customer attitude to estimate the rating of products for recommending products. We classified user groups which have similar preference for each item using implicit user behavior. The preference similarity is estimated using the Cross Correlation Coefficient. Our recommendation technique shows a high degree of accuracy as we use age and gender to group the customers with similar preference. In the experimental section, we show that our method can provide better performance than other traditional recommender system in terms of accuracy.

• The Journal of Information Systems
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• v.14 no.3
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• pp.59-62
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• 2005

The recent broadcasting environment has shifted to embrace multimedia and multi-channel features through terrestrial, satellite and cable media. This has multiplied the number of broadcasting programs. With the information on a myriad of programs provided to TV viewers, information overload occurs, and thus, the TV viewing environment is shifting to one where viewers cannot select programs passively. Thus, a growing need is emerging to ensure a personalized electronic program guide (EPG) to help individuals select TV programs according to their taste. This paper presents a personalized EPG that enables a purpose-oriented broadcasting service to provide personalized broadcasting programs in tune with the user's requirements and preferences.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.305-321
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• 2004

With the advent of the digital broadcasting, the audiences can access a large number of TV programs and their information through the multiple channels on various media devices. The access to a large number of TV programs can support a user for many chances with which he/she can sort and select the best one of them. However, the information overload on the user inevitably requires much effort with a lot of patience for finding his/her favorite programs. Therefore, it is useful to provide the persona1ized broadcasting service which assists the user to automatically find his/her favorite programs. As the growing requirements of the TV personalization, we introduce our automatic user preference learning algorithm which 1) analyzes a user's usage history on TV program contents: 2) extracts the user's watching pattern depending on a specific time and day and shows our automatic TV program recommendation system using MPEG-7 MDS (Multimedia Description Scheme: ISO/IEC 15938-5) and 3) automatically calculates the user's preference. For our experimental results, we have used TV audiences' watching history with the ages, genders and viewing times obtained from AC Nielson Korea. From our experimental results, we observed that our proposed algorithm of the automatic user preference learning algorithm based on the Bayesian network can effectively learn the user's preferences accordingly during the course of TV watching periods.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.45-48
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• 2008

Using these systems, additional information on the paintings and exhibits may be provided in the forms of text, image, speech, and video However, at museums and exhibitions, many tourists are often interested in exhibits of some particular style, authors, or coteries. The proposed Augmented Reality based guidance system may guide the users to exhibits of their interest for selective viewing. Location of the next exhibit of interest may be informed to the users as well as additional multimedia information on the exhibits of interest Such information is shown on the Augmented Reality views of the user's display device. The proposed system is composed an Ultra-Mobile PC (UMPC), an inertia tracker, and a camera. In the beginning, the user may select his/her preference on the exhibits from the menu, and then the system starts guiding by showing the relative orientation, distance, and visual cue to find a next exhibit. When the user finds and locates the matching visual cue within a matching box of the display screen, the system provides multimedia information on the exhibit. According to the preliminary user test, the proposed system is convenient and useful for navigating through large-scale exhibition.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.485-498
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• 2015

The need for forest therapy programs has been increasing. For more effective forest healing, it is necessary to identify the characteristics of participants and develop and operate more targeted and differentiated forest therapy programs accordingly. In this study, the relationships between MBTI (Myers-Briggs Type Indicator) personality types and the relationship between the temperaments of MBTI and the preference for the forest therapy programs were analyzed respectively in pursuit of the basic data required for the effective development and operation of forest healing on the basis of individual characteristics. The survey on the forest therapy program and MBTI personality tests were conducted for 245 normal adults. Using the SPSS 21.0 program analysis, data were analyzed by Analysis of variance (ANOVA) to obtain the difference of preference on the forest therapy program according to the personality type. The Extraversion(E)-Introversion(I) types showed differences in technique-based breathing exercises, walking in the forest(wearing shoes), laughter therapy in the forest, viewing the forest, forest bathing, wind bathing and sun bathing. And the Sensing(S)-iNtuition (N) types had marked differences in listening to the sound of water flowing, drinking herbal tea and sleeping in the forest. The Thinking (T) -Feeling (F) types marked differences in soaking hands and feet in water and sleeping in the forest. The Judging (J)-Perceiving (P) types had differences in vision quest and viewing the forest, respectively, in statistics. Depending on the temperament of the character, there were statistically significant differences in preferences such as drinking herbal tea, eating natural food, sleeping in the forest, viewing the forest and listening to the forest commentary. The results of this study are expected to be used as a basis for forest healing program development and operation.