• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.238-252
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• 2009

Due to the rapid increase of available contents via the convergence of broadcasting and internet, the efficient access to personally preferred contents has become an important issue. In this paper, for recommendation scheme for TV programs using a collaborative filtering technique is studied. For recommendation of user preferred TV programs, our proposed recommendation scheme consists of offline and online computation. About offline computation, we propose reasoning implicitly each user's preference in TV programs in terms of program contents, genres and channels, and propose clustering users based on each user's preferences in terms of genres and channels by dynamic fuzzy clustering method. After an active user logs in, to recommend TV programs to the user with high accuracy, the online computation includes pulling similar users to an active user by similarity measure based on the standard preference list of active user and filtering-out of the watched TV programs of the similar users, which do not exist in EPG and ranking of the remaining TV programs by proposed rank model. Especially, in this paper, the BM (Best Match) algorithm is extended to make the recommended TV programs be ranked by taking into account user's preferences. The experimental results show that the proposed scheme with the extended BM model yields 62.1% of prediction accuracy in top five recommendations for the TV watching history of 2,441 people.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.294-301
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• 2011

The current study examined the influence of current TV health programs on old people's practice of health behaviors through analyzing their recognition, watching behaviors and satisfaction. The study conducted 293 old people living in Pohang City, North Gyeongsang Province from March 17, 2008 to March 28, 2008. The results of this study were as follows: 86.3% of the respondents has watching experience of TV health programs in a month while there was a meaningful difference in frequency of watching by education, obesity and a clinical history. The degree of health behavior practice, 62.1% answered high while 17.7% said low. Factors that influence the degree of health behavior practice were sex, interest in health and experience of watching. In addition, men practiced 1.78 times more than women, those with more interest in health practiced 3.3 times of those with no interest, and those with watching experience presented 6.1 times higher practice degree than those with no experience. It was found that old people's recognition for TV health programs was positive, and the more frequently they watch the programs, the higher their practice of health behaviors was. In addition, old people's popularity rate of TV health programs means that they have a lot of opportunities to be exposed to information provided in health programs. Accordingly, it is thought that TV health programs should try to provide correct health information that can meet old people's needs.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.709-719
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• 2016

This study reviews the so-called 'format-export' of Korean TV entertainment programs to China, and ahalyze its effect on the spread of Hallyu in China. Format export has developed as an alternative for the export of Korean TV programs when the Chinese government restrict the broadcasting of foreign TV programs. In so doing, the study conducted surveys about the format-exported programs in Shanghai and Zhengzhou with the sample of 381 university students. The survey shows that the popularity of entertainment programs is so high as to compete with the popularity of K-pop. Respondents in Zhengzhou tend to watch format-exported programs first and then try to watch original Korean programs, while respondents in Shanghai are more likely to watch original Korean programs. This results suggest that format-export can help the spread of Hallyu in the inland local cities in China.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1357-1364
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• 2010

With the emergence of digital TV broadcasting, various TV channels are provided to a TV audience. But it is getting hard for the audience to find his or her preferred TV programs due to the huge number of TV channels. In order to mitigate the difficulty, channel navigation schemes have been proposed. The schemes predict preferred TV channel from viewer's previous watching histories, and provide the predicted channels when the viewer wants to change TV channel. As channel navigation schemes, there are Most Recently Selected (MRS) scheme providing the most recently watched channel, and Most Frequently Selected (MFS) scheme providing the most frequently selected channel. However, MFS and MRS scheme could be inappropriate to current TV system broadcasting various TV programs in a channel because they are based on the viewer's patterns of watching TV channels. Therefore, this paper proposes an efficient channel navigation scheme, Program Most Frequently Selected (PMFS), based on patterns of watching TV programs instead of TV channels. Simulation results show that the proposed scheme PMFS reduces the seek distance compared to the previous channel navigation schemes, MFS and MRS.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.9-18
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• 2017

In order to respond to the ever-changing media environments in the era of smart and mobile technology, KBS has introduced and partially applied PIE-TV and PIE-nonTV modes that monitor the average number of viewers among the national population group by means of the sample household extraction method which is a traditional way of rating investigation. This study analyzes the correlation between the number of viewers of premiere, re-air broadcasting, and MPP channel programs and the number of OTT-based VOD viewers in reference to the data extracted from PIE-TV survey results. KBS conducted a survey for 3 months between June and August 2017 to measure the PIE-TV Index, based on which the above-mentioned correlation was analyzed with programs classified to entertainment, drama, and cultural programs. For data analysis, SPSS (Ver. 18.0 for Window, SPSS Inc, Chicago, IL, USA) was utilized. It was assumed that when p<0.05 in the confidence interval of 95%, statistically significance would be secured. Among the 30 subjects in the simple correlation analysis, the parameter was determined by the Person correlation coefficient and the non-parameter by the Spearman correlation coefficient. Analysis results are as below: (1) As the number of viewers of premier entertainment, drama, and cultural programs was larger, the number of VOD viewers was larger accordingly. (2) As for entertainment and drama programs, as the number of re-air broadcasting viewers was larger, the number of VOD viewers decreased accordingly. (2) As for entertainment and drama programs, as the number of MPP viewers was larger, the number of VOD viewers decreased accordingly. It is expected that this statistical data can be utilized for strategic planning of MPP channel lineups including terrestrial TV broadcasting, cable TV, etc.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.683-692
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• 2003

The rapid increase of the number of channels makes it hard to find wanted programs from TV. In recent years, the number of channels come up to hundreds with the digital TV arrival. So, it will drive us to the new way of watching TV. In this paper, we introduce a recommendation system for TV programs to overcome this difficulty. We model user profiles and design each module of the system, considering TV environment. Our system gathers basic information from people manually and then updates user profiles automatically by tracking viewing and usage history. As a result, our system recommends daily TV programs based on the changing interest of users. In this paper, we address the problems and solutions by describing our system and the experiment.

• Hwankyungkyoyuk
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• v.19 no.3
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• pp.165-182
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• 2006

Demands for developing diverse teaching methods and materials which can lead to active participation of students in classes have been emerged for environmental education in secondary schools. In order for more effective environmental education, a variety of programs in the mass media including public broadcasting have been used. Advantages associated with the broadcasted TV programs include compensation of temporal and spatial limits embedded with the printing media, improvement of studying efficiency, and provision of diverse studying opportunities, leading to the promotion of the awareness of environmental issues. In this study, 256 environmental issues related TV programs being aired via major public broadcasting companies such as EBS, KBS, MBC and SBS between years of 2003 and 2004 were analyzed. During the present research, selection of the programs was made based on the weight of the environmental issues in independent programs being aired for at least 10 minutes. A survey as a primary means was carried out for the utilization of the audio-visual educational materials in order to provide a new method employing the TV programs which were related to the environmental issues during the instruction in secondary schools.

• Journal of Agricultural Extension & Community Development
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• v.10 no.2
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• pp.229-237
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• 2003

Since the 1960s in Korea, major broadcasting channels broadcasted farm television programs, however, airing of these programs were reduced in the 1990s. This was due to the declining number of farmers, and the low popularity rating of farm television programs. To cope with the situation, agriculture businessmen, farmers, and the officials concerned tried to acquire the independent farming television channel in cable television and satellite television, In 1998, one cable television channel started broadcasting, while another channel in satellite television began its broadcasting in 2001. One of the major concerns of the people in the broadcasting was actualization of the public interests in the new media multi-channel age. Recognizing this point, the study explored a few areas of concern such as conceptualizations of the public interest of the people in the digital age, examination of the surroundings of program production and marketing, and survey the media use behavior of target audience - rural residents; In the concept of the public interest, there are two points of view; market focused and democratic principle oriented. As the digitalization of broadcast advances and the logic of economics prevails, it is difficult to offer the public broadcasting service to farmers, however, democratic principles should be more emphasized. The rural resident prefer major terrestrial television channel to cable television and satellite television channel, and in media use behavior, the medium of major terrestrial television would be more useful for farm broadcasting.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.270-283
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• 2012

With the advent of multi-channel TV, IPTV and smart TV services, excessive amounts of TV program contents become available at users' sides, which makes it very difficult for TV viewers to easily find and consume their preferred TV programs. Therefore, the service of automatic TV recommendation is an important issue for TV users for future intelligent TV services, which allows to improve access to their preferred TV contents. In this paper, we present a recommendation model based on statistical machine learning using a collaborative filtering concept by taking in account both public and personal preferences on TV program contents. For this, users' preference on TV programs is modeled as a latent topic variable using LDA (Latent Dirichlet Allocation) which is recently applied in various application domains. To apply LDA for TV recommendation appropriately, TV viewers's interested topics is regarded as latent topics in LDA, and asymmetric Dirichlet distribution is applied on the LDA which can reveal the diversity of the TV viewers' interests on topics based on the analysis of the real TV usage history data. The experimental results show that the proposed LDA based TV recommendation method yields average 66.5% with top 5 ranked TV programs in weekly recommendation, average 77.9% precision in bimonthly recommendation with top 5 ranked TV programs for the TV usage history data of similar taste user groups.