• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.33 no.3
• /
• pp.267-293
• /
• 2022

A webzine issued by a public institution not only plays a role in communication between members of the institution and its users, but is itself a meaningful record. In addition, as one of the management techniques of the archives, there is a growing awareness that active marketing is needed to promote the service and allow potential users to visit the archives. Therefore, efforts should be made to increase user satisfaction by identifying user needs, composing content reflecting them, and selecting user-centered interfaces appropriately. The purpose of this study is to design 'On-Gi', a newsletter of the Presidential Archives, as a user-participating smart platform in a smart device environment. As a research method, we first looked at the current status of webzine publication by relevant domestic institutions. Next, we compared and analyzed the issue of 'On-Gi' provided by the Presidential Archives and major contents. Based on this, a design model of the webzine for the marketing of the Presidential Archives was proposed. This can be used as a key marketing strategy for the Presidential Archives in the new user environment of technological innovation of smart devices.

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

• Cartoon and Animation Studies
• /
• s.9
• /
• pp.127-142
• /
• 2005

Not only in Korea but throughout the entire world millions of people are in contact with images. Images have become a medium through which to transmit anything from simple visualizations of moving images to knowledge and information. The age of the internet has arisen thanks to scientific development, and the internet generation's acquisition of information is continuously becoming faster. The spectators, ufo must choose amongst the excessive amount of available information, are changing along with it just as quickly. The method of visual transmission has changed to match the demands of the fast-changing pace of the new generation. In order to receive an instantaneous selection amongst much information, the primary requisite is attracting one's attention, and then presenting a corresponding feeling of satisfaction. The early stages of film arose from the desire to capture one's actual situation as it realty is. Unsatisfied with the still picture, people developed the motion picture. Research has succeeded in reproducing 3-dimensional images more realistic than the actual image we perceive as a result of the difference in visual perspective of both eyes and their response to rays of light From color film to 3-dimensional pictures, people enjoy the magnificent results of this. All fields within the category of film are continuously studying the human desire to pursue their visual side, namely the pursuit of visual images with a maximum sense of reality. The images that millions of people around the world see now are flat. The screen's depth and optical illusions effectively give a sense of reality while conveying information. However, although the flat screen is able to create a sense of depth using the different visual perspective of each eye for the realization of a cubic effect, there are limitations. Entering the 21s1 century, there is a quickly-arising branch within the field of image media which seeks to overcome these limitations Although 3-dimensional images began in films, entering the latter half of the 20th century, due to development of 3-dimensional images using the mediums of the animation field, cellular phones, advertisement screens, television etc., without restriction is designated as 'image.'. With research having started around 1900 and continuing for over 100 years, we are now able to witness the popularization of 3-dimensional films happening before our very eyes. Within our own country, we can frequently see them at amusement parks and museums. In the future, through the popularization of HDTV etc., there is a good outlook for practical use of 3-dimensional images in televisions with advanced picture qualify as well as in other areas. Together with the international current, research on 3-dimensional films has been activated in Korea and is rising as a main current in the film industry. Within this context, the contents and understanding of 3-dimensional images must keep in step with the pace of technical advancements. In order to accelerate of development of film contents to keep in pace with technical developments, this dissertation presents the techniques and technical aspects of future developments, and shows the need to prepare in advance to make the field grow- and thereby avoid having a lack of experts and being conquered by other nations in the field - rather than only advancing the technical aspects and importing the contents. This dissertation aims to stimulate interest and continual research by progressive-thinking people related to the film industry. Part II looks into the definition and types of 3-dimensional motion pictures, the terminology, the fundamentals of image formation, current market fluctuations, and looks into 3-dimensional techniques which can be borrowed and introduced in 3-dimensional animations. Part III concerns 3-dimensional animated films. It analyzes 3-dimensional production techniques while using the introduction of specific animation techniques in the 2004 production Lee Sun Shin and Nelson - Naval Heroes 3-dimensional animation produced in 2004 by Clay & Puppet Stop-Motion Animation & Computer Graphic. Original Korean title: 해전영웅 이순신과 넬슨. as an example, and it also looks into how current film techniques used in animations can be applied in 3-dimensional films. Additionally, the actual stages of the various fields of 3-dimensional animations are presented. Given the current direction and advancement of 3-dimensional films making use of animations and the possible realization of this field, the author plans to weigh the development of this yet unexploited new market Not looking at the current progress of the field, but rather the direction of the hypothetical types of animation techniques, the author predicts the marketability and possibility of development of each area.

• Journal of Broadcast Engineering
• /
• v.10 no.1 s.26
• /
• pp.43-56
• /
• 2005

In the existing broadcasting environment, it is not easy to serve the bi-directional service between a broadcasting server and a TV audience. In the uni-directional broadcasting environments, almost TV programs are scheduled depending on the viewers' popular watching time, and the advertisement contents in these TV programs are mainly arranged by the popularity and the ages of the audience. The audiences make an effort to sort and select their favorite programs. However, the advertisement programs which support the TV program the audience want are not served to the appropriate audiences efficiently. This randomly provided advertisement contents can occur to the audiences' indifference and avoidance. In this paper, we propose the target advertisement service for the appropriate distribution of the advertisement contents. The proposed target advertisement service estimates the audience's profile without any issuing the private information and provides the target-advertised contents by using his/her estimated profile. For the experimental results, we used the real audiences' TV usage history such as the ages, fonder and time of the programs from AC Neilson Korea. And we show the accuracy of the proposed target advertisement service algorithm. NDS (Normalized Distance Sum) and the Vector correlation method, and implementation of our target advertisement service system.

• Journal of Intelligence and Information Systems
• /
• v.19 no.1
• /
• pp.57-77
• /
• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.