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

• Journal of Korean Library and Information Science Society
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• v.11
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• pp.69-99
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• 1984

A dramatic development in the new technology of copying materials has presented us with massive problems on reconciling the conflicts between copyright owners and potential users of copyrighted materials. The adaptation to this changing condition led some countries to revise their copyright laws such as in the U. S. in 1976 and in Korea in 1984 for merging with the international or universal copyright conventions in the future. Copyright defined as exclusive rights given to copyright owners aims to secure a fair return for an author's creative labor and to stimulate artistic creativity for the general public good. The exclusive rights on copyrightable matters, generally for reproduction, preparation of derivative works, public distribution, public performance, and public display, are limited by fair use for scholarship and criticism and by library reproduction for its preservation and interlibrary loan. These limitations on the exclusive rights are concerned with all aspects of library services and cause a great burden on librarian's daily duty to provide balance between the rights of creators and the needs of library patrons. The fair use as one of the limitations on it has been coupled with enormous growth of a new technology and extended from xerography to online database systems. The implementation of the fair use and library reprography in Korean law to the local practices is examined on the basis of the new American copyright act of 1976. Under the draft revision of Korean law, librarians will face many potential problems as summarized below. 1. Because the new provision of 'life time plus 50 years' will tie up substantial bodies of material longer than the old law, until that date librarians would need permissions from the owners and should pay attention to the author's death date. 2. Because the copyright can be sold, distributed, given to the heirs, donated, as a whole or a part, librarians should chase down the heirs and other second owners. In case of a derivative work, this is a real problem. 3. Since a work has its protection from the moment of its creation, the coverage of copyrightable matter would be extended to the published or the unpublished works and librarian's work load would be heavier. Without copyright registration, no one can be certain that a work is in the public domain. Therefore, librarians will need to check with an authority. 4. For implementation of limitations on exclusive rights, fair use and library reproduction for interlibrary loan, there can be no substantial aggregate use and there can be no systematic distribution of multicopies. Therefore, librarians should not substitute reproductions for subscriptions or purchases. 5. For the interlibrary loan by photocopying, librarians should understand the procedure of royalty payment. 6. Compulsory licenses should be understood by librarians. 7. Because the draft revision of Korean law is a reciprocal treaty, librarians should take care of other countries' copyright law to protect foreign authors from Korean law. In order to solve the above problems, some suggestions are presented below. 1. That copyright clearinghouse or central agency as a centralized royalty payment mechanism be established. 2. That the Korean Library Association establish a committee on copyright. 3. That the Korean Library Association propose guidelines for each occasion, e.g. for interlibrary loan, books and periodicals and music, etc. 4. That the Korean government establish a copyright office or an official organization for copyright control other than the copyright committee already organized by the government. 5. That the Korean Library Association establish educational programs on copyright for librarians through seminars or articles written in its magazines. 6. That individual libraries provide librarian's copyright kits. 7. That school libraries distribute subject bibliographies on copyright law to teachers. However, librarians should keep in mind that limitations on exclusive rights are not for an exemption from library reprography but as a convenient access to library resources.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.57-75
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• 2019

Soundscapes have the potential to help people experience the historical background and cultural traditions by the scenery of a local area and to be used as a cultural and tourism resource. This concept was first explained in detail by M. Schafer and has been developed as a new way of experiencing landscapes using various senses. This research studied the soundscape of Kyodong Island, the so-called "Island of Peace" and designed new cultural acoustic content for education and tourism. Kyodong Island is located right below the Northern Limit Line and the whole island is in the Civilian Controlled Area. The political and economic status of the island has been changed dynamically by the Korean War and the division of the country. These days, the island needs to realize the vision of the "Island of Peace" in a more creative way using local resources, including its "cold war landscape" and the natural scenery of the region. This research applied the concept of a soundscape to document the island, and to reproduce it in an artistic way. A workshop was conducted to learn concepts and techniques of soundscapes with a sound artist. Listening, recording, conducting interviews, and literature research was used to study the soundscape of the island. After that, this research reconstructed the soundscape of the island through a soundscape composition. The main theme of the composition story was the "Hope and Wish for the Harmony and Peace" to show the vision of the "Island of Peace". The initial sub-theme for the introduction part was "First Encounter with Kyodong Island" arranging the representative soundscape, which could be the first impression of the region. The second sub-theme was "War and Tension" using several soundscapes as a metaphor for the tragedy of the Korean War. The third sub-theme was "Everyday Life of Kyodong Island" which described the energy of the present day, after the wounds of the war have healed. The final sub-theme was "Harmony and Peace" using traditional music and keynote sounds of the region as a reminder of the peaceful past, before the war. The recording files were documented as two types of sound maps. One was a two-dimensional map to show the soundscapes from one point of view, and the other used the online application called "Sound Around You". The final artwork was displayed at an exhibition and uploaded on YouTube to be shared publicly. Through this project, we discovered the potential of soundscapes as a medium to preserve the history and local identity, as well as presenting a new vision. The artwork will be exhibited at historically and culturally meaningful places on the Island to utilize the underused places as local tourist attractions and educational resources.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.