• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.440-443
• /
• 2005

The wide spread of internet business recently necessitates recommendation systems which can recommend the most suitable product fur customer demands. Currently the recommendation systems use content-based filtering and/or collaborative filtering methods, which are unable both to explain the reason for the recommendation and to reflect constantly changing requirements of the users. These methods guarantee good efficiency only if there is a lot of information about users. This paper proposes an algorithm called 'demand articulate & integration' which can perceive user's continuously varying intents and recommend proper contents. A method of knowledge classification which can be applicable to this algorithm is also developed in order to disassemble knowledge into basic units and articulate indices. The algorithm provides recommendation outputs that are close to expert's opinion through the tracing of articulate index. As a case study, a knowledge base for heritage information is constructed with the expert guide's knowledge. An intelligent recommendation system that can guide heritage tour as good as the expert guider is developed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.3
• /
• pp.416-421
• /
• 2008

This paper realizes a system that recognizes traffic safety signs by applying the principle used for game in reverse. The game used for this paper is one that expresses the shape of temporary objects intended by the maker when the maker sees the numerical image provided on (x, y) coordinates and then expresses it on the mesh. After separating the traffic safety sign image from the input image, the system is realized by outputting the content of the sign into letters by recognizing the forms and colors constituting the sign using the puzzle game above. Our system has fast process time and better rate of recognition than the existing system with black-and-white image processing and recognition without any penciling progress.

• Journal of Korea Multimedia Society
• /
• v.22 no.2
• /
• pp.260-270
• /
• 2019

As the growth of developing Islamic countries, Muslims are into the world. The most important thing for Muslims to purchase food, ingredient, cosmetics and other products are whether they were certified as 'Halal'. With the increasing number of Muslim tourists and residents in Korea, Halal restaurants and markets are on the rise. However, the service that provides information on Halal restaurants and markets in Korea is very limited. Especially, the application of recommendation system technology is effective to provide Halal restaurant information to users efficiently. The profiling of Halal restaurant information should be preceded by design of recommendation system, and design of recommendation algorithm is most important part in designing recommendation system. In this paper, an Intelligent Recommendation Service system for offering Halal food (IRSH) based on dynamic profiles was proposed. The proposed system recommend a customized Halal restaurant, and proposed recommendation algorithm uses hybrid filtering which is combined by content-based filtering, collaborative filtering and location-based filtering. The proposed algorithm combines several filtering techniques in order to improve the accuracy of recommendation by complementing the various problems of each filtering. The experiment of performance evaluation for comparing with existed restaurant recommendation system was proceeded, and result that proposed IRSH increase recommendation accuracy using Halal contents was deducted.

• Journal of Information Science Theory and Practice
• /
• v.12 no.2
• /
• pp.79-95
• /
• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• Korean Chemical Engineering Research
• /
• v.56 no.4
• /
• pp.453-460
• /
• 2018

Owing to rising oil prices and anthropogenic global warming, focused attempts are being made toward production of industrially important compounds by using renewable biomass. In this context, algal biomass as third-generation biomass is important because it doesn't compatible with food resource, has high yield, and helps abate greenhouse gases. Here, we investigate whether Undaria has the highest sugar content, which would make it the most suitable biomass for lactic acid production among the four algal biomasses tested. For effective pretreatment of Undaria, the response surface methodology was used. The amount of solid loaded and catalyst concentration were related to the extraction rate of total sugar. Lactic acid was produced by pretreatment of Undaria by using four Lactobacilli, and L. alimentarius and L. brevis were found to be suitable for lactic acid production.

• Journal of Digital Convergence
• /
• v.18 no.7
• /
• pp.73-84
• /
• 2020

The whole world is making a variety of efforts to cope with the revolutionary changes in the economy and society that are emerging from intelligent information technology. Therefore, this study defined national public officials' intelligence information competency in the intelligent information society, and tried to derive competency clusters and sub-elements. To achieve this objective, this study explores literature research about bloom's digital taxonomy, information competency, and national ICT policies and national public officials' intelligence information competency was defined based on bloom's digital taxonomy perspective was modified and supplemented with this study and provisional constituent elements of competency were derived. In addition, 5 experts verified the content validity. As a result, 7 competency clusters and 22 sub-elements are finally derived. The findings of this study are expected to be useful as the basis for the national intelligence information human resource development.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.3
• /
• pp.337-342
• /
• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.1-28
• /
• 2022

In recent years, many Internet giants have begun providing their own content services, which attract online users by offering personalized services based on artificial intelligence technologies. This study investigates the role of two firms' content services within the firms' online service network. We examine the role of Naver Webtoon, which can be characterized as a professional-generated content, within Naver's service portfolio, and that of Google YouTube, which can be characterized as a user-generated content, within Google's service portfolio. Using survey data on viewers' use of the two services, we analyze a valued directed service network, where a node denotes an online service and a relationship between two nodes denotes a sequential use of two services. We found that both Webtoon and YouTube show higher out-degree centrality than in-degree centrality, which implies these content services are more likely to be starting services rather than arriving services within the firms' interactive network. The gap between the out-degree and in-degree centrality of YouTube is much smaller than that of Webtoon. The high centrality of YouTube, a user-generated content service, within the Google service network shows that YouTube's initial role of providing specific-content videos (e.g., entertainment) has expanded into a general search service for users.

• Journal of Intelligence and Information Systems
• /
• v.14 no.2
• /
• pp.157-177
• /
• 2008

Even in a single day, an enormous amount of content including digital videos, posts, photographs, and wikis are generated on the web. It's getting more difficult to recommend to a user what he/she prefers among these contents because of the difficulty of automatically grasping of content's meanings. CF (Collaborative Filtering) is one of useful methods to recommend proper content to a user under these situations because the filtering process is only based on historical information about whether or not a target user has preferred an item before. Collaborative Tagging is the process that allows many users to annotate content with descriptive tags. Recommendation using tags can partially improve, such as the limitations of CF, the sparsity and cold-start problem. In this research, a CF method with user-created tags is proposed. Collaborative tagging is employed to grasp and filter users' preferences for items. Empirical demonstrations using real dataset from del.icio.us show that our algorithm obtains improved performance, compared with existing works.

• Journal of Internet Computing and Services
• /
• v.13 no.5
• /
• pp.45-53
• /
• 2012

The appearance of Intelligent mobile and home appliance increased the using of not only various multimedia contents but also educational contents. Especially the growth of smart device such as smart phone, smart pad and smart TV, provided the environment which everyone can use educational content anytime, anywhere, any device. However many smart devices are hard to reuse the various educational contents because the devices and mobile os policies are not unify. In this paper, we suggest the design of NeS(N-Screen e-learning system) in order to solve this problem. NeS is consisted of User Management, Educational Content Management, Content Convert System and Interactive Management System. In this system, we use the HTML5 language to assure interoperability in various Smart Device Environment. Through NeS, we can achieve Content OSMU(One Source Multi Use) in various device environment and assure the continuity of the contents for using the educational contents more easily.