• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Korean Library and Information Science Society
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• v.39 no.3
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• pp.321-344
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• 2008

This study tries to compare the classification systems of major internet portals and their sub-portals specialized for the children and of major online book stores. It compares and analyzes the major directories of them and suggests recommendations not only to improve their own systems but also to apply to the development for the classification systems for children's library. Some of them are: (1) The system should reflect information requests and use behaviors of the children netizen. (2) It should select the terms reflecting the children's viewpoints and expressions and suggest the guidelines by ages. (3) It should maintain the clear hierarchies and grouping for the accessability and convenience of the users. (4) It will be helpful to establish the categories to mix the subject- or concept-based categories and the activities and objects of the children. (5) It will also be helpful to establish the categories based on the curricula added by those creating the imagination and interest and to subdivide by subject.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.701-707
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• 2011

The aim of this paper is to develop a collaborative design system that can facilitate remote modification and control of a 3D solid model through the Internet. It enables the users to resolve conflicting viewpoints about an issue and collaborate to design a tangible object within a given set of constraints. In order to optimize the collaborative design system, we focus on the results obtained by using the collaborative design method for the real-time modification of a 3D solid model in a distributed environment. It also provides the method of managing the consistency between design entities. The efficiency of the system is verified by implementing it in a distributed environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.703-711
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• 2018

Recently, as various metro lines have been constructed and connected to other lines the rate of utilization has also been increased. However, the existing fare policy which the government does still stick to causes not only inappropriate action to the demand pattern but aggravation of the profit of the operation company. This study reviewed rail fare policy of major countries such as Japan and U.K etc. to improve the rationality of fare policy in Korea. In order to systematical analysis of fare policy, such viewpoints as of fare decision method, the card fare discounting system, the structure of fare, and the government subsidy policy were reviewed. Based on the results from the review, various problems and improvement plans were drawn. Through this study, appropriate fare systems to urban railway users could be given to improve the chronic deficit problem of urban railway operators.

• The Journal of Korean Association of Computer Education
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• v.10 no.5
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• pp.1-9
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• 2007

Although the need for overall amendment of curriculums recognized, tentative plan for amendment is being established without improving the sense of satisfaction of the users of curriculums from the nation-wide dimension and without review on philosophical and educational psychological viewpoints on curriculum with focus on curriculums that reflects the national and social demands until the tentative plans for amendment of computer subject is made at the time of amendment. Therefore, new/old curriculums has been compared and analyzed from philosophical and psychological viewpoint of curriculums in order to definitively establish status and identity of curriculum, and to cope with changes in educational system. It can be seen from the outcome of such comparative analysis that goals of the philosophical viewpoint of amended curriculum had been defined as discipline-centered curriculum while that for the knowledge-based viewpoint on constructivism and cognitivism.

• Journal of Digital Policy
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• v.2 no.2
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• pp.1-6
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• 2023

This thesis was developed so that users can access tourism services more easily by utilizing Unity based on the metaverse. The core function and environment of the program were created using Unity, a game production tool, to create a virtual space. In the virtual space, it is implemented so that the tourist service can be used from various angles and positions through NPCs to which control and camera viewpoints are applied. This project is a content that allows you to visit tourist attractions in a virtual world without going to the site by using virtual reality technology. The background and goal of the project is to make it into a game form using a UI frame and fuse it into a simple game form to add fun elements to enable virtual reality tourist experience applying game for tourist attraction publicity.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.150-157
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• 2009

In this paper, we propose a person tracking based multi-channel audio panning system for multi-view broadcasting services. Multi-view broadcasting is to render the video sequences that are captured from a set of cameras based on different viewpoints, and multi-channel audio panning techniques are necessary for audio rendering in these services. In order to apply such a realistic audio technique to this multi-view broadcasting service, person tracking techniques which are to estimate the position of users are also necessary. For these reasons, proposed methods are composed of two parts. The first part is a person tracking method by using ultrasonic satellites and receiver. We could obtain user's coordinates of high resolution and short duration about 10 mm and 150 ms. The second part is MPEG Surround parameter-based multi-channel audio panning method. It is a method to obtain panned multi-channel audio by controlling the MPEG Surround spatial parameters. A MUSHRA test is conducted to objectively evaluate the perceptual quality and measure localization performance using a dummy head. From the experiments, it is shown that the proposed method provides better perceptual quality and localization performance than the conventional parameter-based audio panning method. In addition, we implement the prototype of person tracking based multi-view broadcasting system by integrating proposed methods with multi-view display system.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.302-315
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• 2020

The issue concerning how to integrate with the needs of sustainable development according to Crime Prevention Through Environmental Design(CPTED) theory still continues in the development process of the third-generation theory at the present stage. In addition, the issue is under worldwide controversy and discussion. What is more noteworthy is that the viewpoints under debate and discussion have an influence on the mutual effect and relationship between the theoretical model and the principles in the theoretical model, and the influence can never be underestimated. After a mastery of the overall context of theoretical development, it is believed in this study that the identity of CPTED theory development can provide a diverse understanding dimension and a communication method between the environment and environmental users. On the basis of identity the development of CPTED theory, the crime prevention design mode of CPTED needs to connect different dimensions of sustainability, with the design goal of livability as the starting point, the Top-down model to adjust the safety of the environment. By no means can the environmental condition be improved by solely relying on the previous physical design method in virtue of Bottom-up model. Therefore, in this study, the identity of CPTED will be set as the core combined with Top-down crime prevention design model to propose a visual proposal for the reconstitution of the theoretical model, rather than supplementing the application of the contents or principles at a certain stage. Hence, it is expected to provide reference and enlightenment for the sustainable development of CPTED theory.