• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1223-1233
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• 2002

Recently various electronic books (I-Book) based on PDA (personal digital assistance) that we can easily use anytime and anywhere have been developed. Volume and weight of the E-Book is much less than that of traditional books. In that reason, it is easy to carry and serve us with contents by diverse functions such as searching, bookmark, dictionary, and playing of color image, sound or moving picture. On account of these advantages, many products connected with I-Book have been emerged in the market. However a product connected with educational contents is scarce, because it requires not only normal function but also additional functions such as a problem solving. Therefore it is actually necessary to develop a browser and an editor for educational contents. In this paper, we express educational contents by XML and define structure of document with XML schema. Then, we design and implement an editor and a browser that can manage educational contents on PDA.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of the Korea Computer Graphics Society
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• v.12 no.4
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• pp.23-32
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• 2006

In recent years, since the digital camera has been popularized, so users can easily collect hundreds of photos in a single usage. Thus the managing of hundreds of digital photos is not a simple job comparing to the keeping paper photos. We know that managing and classifying a number of digital photo files are burdensome and annoying sometimes. So people hope to use an automated system for managing digital photos especially for their own purposes. The previous studies, e.g. content-based image retrieval, were focused on the clustering of general images, which it is not to be applied on digital photo clustering and classification. Recently, some specialized clustering algorithms for images clustering digital camera images were proposed. These algorithms exploit mainly the statistics of time gap between sequent photos. Though they showed a quite good result in image clustering for digital cameras, still lots of improvements are remained and unsolved. For example the current tools ignore completely the image transformation with the different focal lengths. In this paper, we present a photo considering focal length information recorded in EXIF. We propose an algorithms based on MVA(Matching Vector Analysis) for classification of digital images taken in the every day activity. Our experiment shows that our algorithm gives more than 95% success rates, which is competitive among all available methods in terms of sensitivity, specificity and flexibility.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.1-25
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• 2023

This study aims to propose implications for the development of archival content of archives management institutions in Korea by analyzing cases of the archival content on Instagram of the national archives in the Anglosphere. The basic information of the research target's Instagram account, including the creation date, content, and the number of followers, was investigated, and the posts' contents and interaction types with high user responses were analyzed. As a result, to spread the records information service using Instagram, producing images and short-form content that can be intuitively checked through mobile screens and creating content that will attract the attention of primary users are required. Moreover, it is necessary to develop content for informative communications that can be shared with other users. There is also a need to enhance the exposure and searchability of the institution's Instagram account by strengthening connections with the institution's existing online resources and enabling communications, such as using hashtags, following related institutional accounts, and providing feedback on the contents' comments with followers. This study is meaningful in that it examined cases of archival content for Instagram and suggested their applications, and it can be used as basic data to help plan archival contents to spread the archival culture.