• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2002.08a
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• pp.99-108
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• 2002

Since the introduction of carbonated drinks in the 1950s, 'cola' and 'cider'along with orange juice, the dominator of the juice market, have been two main streams of the Korean beverage market. This market pattern has caused the following effects; a. Economical loss due to the import of foreign brands - royalty payments to x company. b. Loss of opportunity to develop a domestic beverage market. c. Inflow of an unfiltered foreign culture. This study shows a change in the Korean beverage market. In the 1980s. consumers' tastes started to change as a trend of developing beverages using traditional Korean ingredients started to begin. On the basis of this change, I would like to discuss the desirable path in developing beverages using traditional ingredients. 'Traditional ingredients'refers to the ingredients that the Korean people have enjoyed within the course of their life, whether it be via food or beverage. These ingredients have been chosen by our people as first rate for centuries. How to modernize and develop these work-in-progress products is the desirable direction for the development of drinks using traditional Korean ingredients. This study also shows various examples of how Korean traditional ingredients and the Western scientific civilization can fuse together to develop a modern and value-added product. One project in particular, created a method of producing a beverage using rice a simple traditional ingredient, marking it a hit product. Through this example, I present the desirable direction of how to develop a modernized drink using traditional ingredients that can change both the consumers' current value on the Korean beverage market as well as create a new pattern of consumer tastes.

• Preventive Nutrition and Food Science
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• v.18 no.4
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• pp.280-286
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• 2013

Despite well established health benefits, today's children do not eat enough vegetables. The purpose of this study was to determine the association between the number of unfamiliar foods in the vegetable food group and the preference for these foods and dietary factors. Subjects were 1,072 children in 5th and 6th grades from elementary schools located in 4 cities in Gyeonggi-do, Korea. A two-page questionnaire consisted of questions asking about the subjects' preference and familiarity for 64 foods in the vegetable group, preferences for three fast foods, four types of vegetable dishes, and six tastes. Also included in the questionnaire were questions assessing subjects' adherence to national dietary guidelines. The subjects were divided into quintiles according to the number of unfamiliar vegetables; the 1st quintile (N=226) was children who had less than 14 unfamiliar vegetables and the 5th quintile (N=229) was more than 29. Compared to the children in the other quintiles, the children in the 5th quintile had a significantly lower adherence to national dietary guidelines regarding consumptions of vegetable and protein sources, regular exercise, awareness of desirable height and weight, and reading food labels, as well as total (P<0.05). The preferences for bland tastes (P<0.05), salads (saengchae, P<0.01), stir-fried vegetables (P<0.01), and several vegetable items (P<0.05) were significantly lower in the 5th quintile compared to the other quintiles. This study proposes the potential benefits of teaching children names of a variety of vegetables to improve their dietary factors such as food preferences and dietary habits.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.554-559
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• 2006

The currently common housing is obviously going to be under the reconstruction in just $20{\sim}30$ years, with the failure to satisfy the improvement of national income, diversification and advance of national demand. But, reckless and random reconstruction Induce the serious problem of environmental pollution involving the loss of national treasury and excess materials of constructions. In order to address such problem, the common housing of longevity, which can adequately cope with the changes of times and tastes of inhabiters, in the future, is arising as an alternative. Recently, the groundbreaking phase of common housing is also being considered as another alternative to resolve such problem. The common housing of longevity has an advantage to create a free and comfortable space in accordance with the tastes of inhabiters, as well as expanding the durability of building. But, the current facility system has an inability to deal with the sort of housing. Thus, the research paper is designed to make an analysis on problems of common housing in South Korea, which has made it difficult to handle a changing space, and based on the analysis, the paper is intended to make a review on the future-oriented facility service appropriate enough to deal with the changing aspects of space.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.1
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• pp.49-63
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• 2023

The purpose of this study is to investigate the current status and motives of buying second-hand clothing among university students and to suggest a plan to activate second-hand clothing transactions. In order to discover the effect of the buying motives on the purchasing of second-hand clothing, 112 university students who have purchased second-hand clothing over the past six months were surveyed and their responses were used for analysis. As a result of the analysis, it was found that design differentiation, habitual use, and economical factors had a meaningful effect on the purchase of second-hand clothes. Second-hand clothes have a positive environmental perception, but that perception did not impact the purchasing of second-hand clothes. It is necessary to raise the awareness and social movement around second-hand clothing and teach consumers the environmental benefits and sustainability of second-hand clothing. An activation plan for the second-hand clothing market is: 1. Proposes various market subdivisions that meet the characteristics and tastes of consumers that lead to the purchase of used clothing. In this study, two economic factors were found among the buying motives. The first is purchasing second-hand clothing at a very low price, and the second is finding luxurious expensive items or unique values at a lower price. Therefore, it is necessary to find various markets segments that suit consumer tastes by checking consumer characteristics and detailed factors. 2. Nurture second-hand clothing processing brands for the diversification of the second-hand clothing market. 3. There is an urgent need for quality classification, quality assurance, and the standardization of second-hand clothing. This study is meaningful in that it explored the possibility of having a positive effect on activating the second-hand clothing market.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.1
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• pp.83-96
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• 2023

The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

• Information Systems Review
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• v.25 no.4
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• pp.67-87
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• 2023

Many online shopping sites now offer personalized recommendation systems to improve consumers' shopping experiences by lowering costs (time, cost, etc.), catering to consumers' tastes, and stimulating consumers' potential shopping needs. So far, domestic and foreign research on the personalized recommendation system has mainly focused on the field of computer science, which is advantageous for obtaining accurate personalized recommendation results for users but difficult to continuously track the users' psychological states or behavioral intentions. This study attempted to investigate the effect of the characteristics of the personalized recommendation system in the online shopping environment on consumer perception and purchase intention for consumers using the Stimulus-Organism-Response (S-O-R) model. The analysis results adopted all hypotheses on the effect of the quality of the personalized recommendation system and information quality on trust and perceived value. Through the empirical results of this study, the factors influencing consumers' use of personalized recommendation system can be identified. In order to increase more purchase, online shopping companies need to understand consumers' tastes and improve the quality of the personalized system by improving the recommendation algorithm thus to provide more information about products.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.5
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• pp.1341-1345
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• 2007

There are four kinds of formulas for purging the liver to cure its sthenic syndrome based on the types of preparation formulas : Sagan-tang, Saganhwan, Saseem-san and Saganeum. Another formula called Sacheonghwan, Sacheong-tang and Sacheong-san is to purge the green colour of liver. There are 38 kinds of Sagan-tang, 2 kinds of Saganhwan, 29 kinds of Sagan-san, 5 kinds of Saganeum, 4 kinds of Sacheonghwan, 3 kinds of Sacheong-tang and 1 kind of Sacheong-san. Combination of herbal medicines, carried out in formulas for purging the liver, consists of various kinds depending on medical scientists' personal experience in medical treatment without any general principles, which makes it difficult to apply it to clinical use. The objectives of this study lie in theoretical establishment of Sagan-tang for curing the sthenic syndrome of liver through analyzing the component medicines and combination principles of Hyeongok's Sagan-tang, and furthermore, maximizing the clinical use of Sagan-tang. This study analyzed the component medicines and combination principles of Hyeongok's Sagan-tang based on the theory for properties and tastes of herbal medicines from the ${\ulcorner}$Yellow Emperor's Canon of Internal Medicine${\lrcorner}$, the theory for principal herbal medicine, assistant herbal medicine, adjuvant herbal medicine, dispatcher herbal medicine, and the five elements doctrine. Hyeongok's Sagan-tang is an odd prescription, composed of 7 kinds of ingredients : No.1 Radix Paeoniae (2don;7.5 g), No.2 Fructus Chaenomelis (1don;3.75 g), No.3 Radix Rehmanniae (1don), No.4 Folium Phyllostachydis Henonis (1don), No.5 Radix Bupleuri (1don), No.6 Radix Scutellariae (1don), and No.7 Radix Glycyrrhizae (1don). There are three methods for curing the sthenic syndrome of liver according to the five elements doctrine : purging the liver, purging the heart and invigorating the lung. In the case of taste purgation, two herbal medicines with sour taste, Radix Paeoniae and Fructus Chaenomelis, are combined into the principal and assistant herbal medicine, respectively. For property purgation, two herbal medicines with the cool property, Radix Bupleuri and Radix Scutellariae, are combined into adjuvant herbal medicines. Both sweet and cold herbal medicines, Radix Rehmanniae and Folium Phyllostachydis Henonis, are combined into adjuvant herbal medicines. Sour herbal medicines, Radix Paeoniae and Fructus Chaenomelis, were combined to invigorate the lung. Cool herbal medicines, Radix Bupleuri and Radix Scutellariae, were combined to invigorate the lung and to purge the liver. In addition, Radix Glycyrrhizae are combined as dispatcher herbal medicine, harmonizing all the herbal medicines composing the formula. First, to cure the sthenic syndrome of the liver, the methods of purging the liver and the heart, and invigorating the lung should be used according to the five elements doctrine. Secondly, herbal medicines appropriate for those treatment methods should be chosen according to the theory for properties and tastes of herbal medicine and thirdly, the combination of those herbal medicines should be carried out according to the theory for principal herbal medicine, assistant herbal medicine, adjuvant herbal medicine, dispatcher herbal medicine. As a good example, Hyeongok's Sagan-tang is combined according to the above theories.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used