• 정보기술과데이타베이스저널
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• 제1권1호
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• pp.63-81
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• 1994

The trigger mechanism in active object-oriented database systems is known to be a good tool for describing user-defined integrity constraints. It cannot adequately support, however, certain integrity constrains specified on the objects in class composition hierarchy. Those are the cases where the constraints must be maintained in the forward direction along the composition hierarchy as well as in the backward direction We call theses kinds of problems "backward propagation problem" and investigate several ways to resolve them using the currently available techniques. Based on them, a new constructor, called CONSTRAIN $T^{cch}$, is proposed. The constructor can be realized with enhanced facilities for active OODBMS which we recommend in this paper.d facilities for active OODBMS which we recommend in this paper.r.

• 가정과삶의질연구
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• 제15권1호
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• pp.213-224
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• 1997

Emergency funds are usually identified as liquid assets because they are easily and quickly converted to cash for the needs of unexpected expenses. Empirical studies spplirf got American Households have found that most households do not have recommend levels of liquid savings and an analysis of the 1990 survey of consumer expenditures confirms revious findings. Family Income and Expenditure Survey in Korea is the data base for this study and the level of emergency fund as a flow asset is investigated. A three period model of optimal consumption is presented. The results suggest that many consumers who do not have the recommend levels of liquid assets may be acting rationally. The results may be useful for financial counselors and educators. as well as for insight into empircial patterns of savings.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.386-388
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• 2003

We are developing a web-based movie recommender system that catches and reasons with user profiles and ratings to recommend movies. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide effective recommendations. Social recommender systems collect ratings of items from many individuals and use nearest-neighbor techniques to make recommendations to a user. However, these methods only depend on the ratings and ignore other useful information. Our primary concern is to provide an approach that can recommend the movies based on not only the user ratings but also the significant amount of other information that is available about the nature of each items - such as cast list or movie genre. We experimentally evaluate our approach and compare them to conventional social filtering, which suggests merits to our approach.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1997년도 춘계학술대회논문집
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• pp.90-94
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• 1997

Many workers like welders are working in squat sitting postures with te object on the ground for an entire work shift. It is suspected that such prolonged squat sitting without any supporting stool would gradually cause musculoskeletal injuries to workers. This study is to quantitatively evaluate the physical stress caused by the prolonged squat sitting and to recommend a safe work/rest schedule for the task with squat sitting posture based on the lab experiment. In this study, 8 healthy student subjects participated in the experiment. They maintained a squat sitting posture for 16 minutes with 4 different stool height conditions: no stool, 10cm hight, 15cm height, 20cm height. Every 2 minutes, the discomfort was subjectively assessed using the magnitude estimation method for the whole body, lower back, upper leg and lower leg. Based on discomfort rating, we found that 10cm height stool relieved the workload most. Discomfort rating results also indicated that 20cm height stool showed the heghest workload, and that there was no difference in workload between 15cm height and no stool. We recommend to provide the workers with 10cm height stool for prolonged squat sitting tasks.

• International Journal of Advanced Culture Technology
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• 제8권3호
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• pp.325-333
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• 2020

In the past, eating outside was usually the purpose of eating. However, it has recently expanded into a restaurant culture market. In particular, a dessert culture is being established where people can talk and enjoy. Each consumer has a different tendency to buy chocolate such as health, taste, and atmosphere. Therefore, it is time to recommend chocolate according to consumers' tendency to eat out. In this paper, we propose a chocolate recommendation application based on the tendency to eat out using data on social networks. To collect keyword-based chocolate information, Textom is used as a text mining big data analysis solution.Text mining analysis and related topics are extracted and modeled. Because to shorten the time to recommend chocolate to users. In addition, research on the propensity of eating out is based on prior research. Finally, it implements hybrid app base.

• 디지털산업정보학회논문지
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• 제6권2호
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• pp.1-9
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• 2010

The increasing popularity of mobile devices, such as cellular phones, smart phones, and PDAs, has fostered the need to recommend more effective information in ubiquitous environments. We propose the recommendation method for mobile contents service using contexts and prefetching in ubiquitous environment. The proposed method enables to find some relevant information to specific user's contexts and computing system contexts. The prefetching has been applied to recommend to user more effectively. Our proposed method makes more effective information recommendation. The proposed method is conceptually comprised of three main tasks. The first task is to build a prefetching zone based on user's current contexts. The second task is to extract candidate information for each user's contexts. The final task is prefetch the information considering mobile device's resource. We describe a new recommendation.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.93-99
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• 2019

It is a wine recommendation application service designed for people who sometimes drink wine but lack information and have no place to recommend. This study is to develop UI display design method of wine recommendation service using chatbot. The research method was a case study on Korean wine market, a case study on artificial intelligence market, SWOT analysis of wine-related chatbots, and a competitor analysis of related industries. In addition, surveys and in-depth interviews examined the level of interest and understanding of chatbots, and what kind of chatbots they had encountered and what requirements and goals they faced. After grasping the needs and requirements of users, we created a service concept sheet according to them and produced an application UI design that users can use most easily. Therefore, this study is meaningful in that it proposes a UI design that can search wine information more sophisticated and convenient than face-to-face communication through artificial intelligence service called chatbot and recommend wines that match the taste.

• 한국건축시공학회지
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• 제3권3호
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• pp.91-97
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• 2003

At present, the antiwashout underwater concretes are used as popular construction materials in European countries, the United States and Japan. The water-soluble polymers in the antiwashout underwater concretes provide excellent segregation or washout resistance, self-compaction and self-leveling property to the concretes. The purpose of this study is to recommend to optimum mix proportions of antiwashout underwater concretes according to compressive strength of 300kgf/$\textrm{cm}^2$ to 500kgf/$\textrm{cm}^2$. The antiwashout underwater concretes are prepared with various unit cement content, unit water content, sand-aggregate ratio, unit antiwashout agent and superplasticizer content. And they are tested for flowability, and compressive strength. From the test results, it is possible to recommend the optimum mix proportions of antiwashout underwater concretes according to compressive strengths within the range of 300kgf/$\textrm{cm}^2$ to 500kgf/$\textrm{cm}^2$.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 춘계학술대회
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• pp.232-239
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• 2005

Collaborative-filtering-enabled Web sites that recommend books, CDs, movies, and so on, have become very popular on the Internet. Such sites recommend items to a user on the basis of the opinions of other users with similar tastes. This paper discuss an approach to collaborative filtering based on the Simple Bayesian and apply this model to two variants of the collaborative filtering. One is user-based collaborative filtering, which makes predictions based on the users' similarities. The other is item-based collaborative filtering which makes predictions based on the items' similarities. To evaluate the proposed algorithms, this paper used a database of movie recommendations. Empirical results show that the proposed Bayesian approaches outperform typical correlation-based collaborative filtering algorithms.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 춘계학술대회
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• pp.131-138
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• 2005

Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Most of the existing recommender systems focused on what kind of items to recommend, although when to recommend to the target customer considering their context is an important issue. Even right item might be a spam advertisement or wrong recommendation for the customer if it can not be recommended at the right context. It is particularly important for recommendations where the user's context is changing rapidly, such as in both handheld and ubiquitous computing environment. Therefore, we propose CARS (Context-Aware Recommender System) based on CBR and context-awareness for ubiquitous computing environment. CBR is used to generate a target customer class and proper context. Context-awareness is used to gather suer context information from sensors, networks, device status, user profiles, and other sources. An illustrative case example is suggested to explain the procedure of CARS.