• Asia pacific journal of information systems
• /
• v.18 no.3
• /
• pp.123-145
• /
• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Current Industrial and Technological Trends in Aerospace
• /
• v.8 no.2
• /
• pp.76-85
• /
• 2010

This paper discusses recent development trends of fiber optic gyroscope (FOG) in space application. Fiber optic gyroscope utilizes Sagnac effect to measure the angular rate of a rotating object in space. Having a rather short development history compared to ring laser gyroscope (RLG), the fiber optic gyroscope, owing to the emerging technologies in fiber optic society and the digital signal processing technique, reveals itself as a noteworthy replacement of the ring laser gyroscope in the space mission. This paper summarizes the current trends of fiber optic gyroscope based on the actual products commercialized in the market over the last decades, while presenting the future development trends of the fiber optic gyroscope in the space exploration.

• Journal of the Korea Furniture Society
• /
• v.26 no.4
• /
• pp.346-355
• /
• 2015

It suggests a closet design for infants in consideration of space utilization, furniture arrangement, and goods storage by integrating a baby's closet and toy chest, which was used for storage of baby's toys and play instrument. For this, it conducted and analyzed data research on the infants' toy chests in the domestic and overseas market and based on such approach, the colors that helped development of infants' cognition and emotion were selected while suggesting familiar animal characters for infants. Without considering separate arrangement of furniture and toy chest within limited space, it allowed space utilization and provided enough storing space. Also, the attached ball casters enabled easy carry of the closet and with this function, it helps infants arrange and store goods by themselves so that making them feel a sense of accomplishment. For effective spatial utilization as well as security of its genuine storage function, the closet and toy chest were combined in this study. Thus, it is believed that development of such multifunctional furniture will suggest the direction of researches on domestic furniture development that are conducted to maximize utilization of residential space for the people living today.

• Korean Institute of Interior Design Journal
• /
• v.19 no.3
• /
• pp.154-161
• /
• 2010

Domestic distribution environment in Korea has rapidly and qualitatively been developed due to the open of distribution market. However, the function of commercial establishment goes beyond the place value that simple transaction of capacity takes place, and it is recognized as life groove space enhancing the satisfaction of costumers' purchasing pattern. For this reason, there has been the need to change the purchasing environment of commercial space. The change factors of commercial space contributed to the establishment of consumption identity formed by change of consumers' lifestyle and the purchasing pattern. It is necessary to see the change factors of the purchasing pattern as the conversion of distribution environment in terms of supplier and as the change of consumers' lifestyle in terms of consumers. In reality, however, the commercial facility ill-imitated the advanced model and qualitatively was developed. In this situation, the change of the purchasing pattern according to the conversion of facility is needed as an early stage. The purpose of this study is to analyze the overflow supply of commercial facility. Also It will discuss the plan characteristics of commercial space conversion of facility conforming to the change of the purchasing pattern that is predicted in the lifestyle on a conversion stage of facility.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.1-21
• /
• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• The Korean Journal of Air & Space Law and Policy
• /
• v.23 no.2
• /
• pp.173-205
• /
• 2008

Space debris have frequently caused damage to space objects like satellites in orbits and sometimes have fallen on the earth. Such increase in space debris will lead to the high possibility of threatening space activities of mankind. However, it is not so easy for the damage caused both by identified and by unidentified space debris to be recovered since in the regime of the current international law, there is no legislation of prescribing the damage done by space debris. For overcoming the limitation it seems desirable that either the Liability Convention should partly be amended or new international law regime should be established. For instance, 'space debris' should be included in the new definition of 'space object' and the range of launching should also be defined clearly by making the concept of 'launching' somewhat more specified. Moreover, the subject of international liability for damage caused by space debris should be divided into two classes: the subject before and after registration. While in case of before-registration launch states should be held liable for any damage jointly or individually, in case of after-registration 'the state of registry' or 'owner' of the space debris should be. In the event of damage being caused elsewhere than on the surface of the earth to a space object of other State, 'fault-based liability' is currently applied. But it needs to be changed into 'absolutely liability'. In this paper, 'Liability Pool', 'Insurance', 'Market-Share Liability' are presented as aid devices of the damages resulting from unidentified space debris. They should be defined through the amendment of the Liability Convention or another international treaty. Some day there comes a time when our country shall possess many of the astronomical price of satellites. It means that we can't be free from the damage by the increasing number of space debris. Provided that our satellites are damaged by such space debris, it will do the satellites damage and cause impaired functioning or troubles in operation. As a result, if we are not paid for the damage by space debris, we will be confronted with tremendous economic loss because it is necessarily connected with the excess burden of taxation. Thus, an international agreement regarding the measures of the compensation for space debris damage must be made very soon.

• The Journal of Art Theory & Practice
• /
• no.1
• /
• pp.93-108
• /
• 2003

The aim of this thesis is to evaluate visual arts policy during Kookmin government period(1998-2002). In the beginning, many artists had expected president Kim Dae Jung to enlarge arts support But the evaluation of them was very negative because the government was only interested in the development of cultural industry. First, I analysed the government expenditure in the visual arts. Department of Culture and Tourism took the responsibility of visual arts policy. The budget of arts and culture increased to 1 % of total government expenditure in this period. But the main factor was the increasement of cultural industry and tourism expenditure. The budget of visual arts in 2002 was only 6,600million won. Second, I analysed visual arts support programs. (1) The government introduced studio programs for the first time. For 5 years, 2 national studios and 23 public studios were established. (2) The number of art museum was increased to 62. (3) It introduced alternative space support program and supported 200million won annually. (4) Percent for art scheme reduced from 1% to 0.7% of total construction cost, but still 27 public sculpture gardens were built. (5) Business support for visual arts reduced because of IMF. (6) Also arts market froze and many commercial galleries were closed. (7) In order to revitalize region through arts and to promote international exchange of culture, Gwangju Biennale was created. Third, I analysed Arts Plan 2002. It had a radical limitation because it was established in the last year of Kookmin government period. Also it showed special favors to some arts organizations. In general, I think that positive outcomes are the introductions of the studio program and the alternative space support program. Especially alternative space support program enforced the diversity of visual arts, and encouraged creative young artists. But policy of arts market failed because of IMF and visual artists had to go through rough times.

• Korean Institute of Interior Design Journal
• /
• v.23 no.3
• /
• pp.193-203
• /
• 2014

In a rapidly changing market, the companies are applying a variety of elements for promoting sales for the inflow of consumers. For the elements of sales promotion, the tendency to apply the experiential marketing that provides a positive recognition centering on the customers, and in such tendency, the consumers places the values on the experience obtained from the spatial elements of sales promotion provided by the companies. As it is reflected on the life style of consumers, the drugstores applied with the experiential marketing as a mean of sales promotion is rapidly growing in the distribution market. In this study, the elements of sales promotion was picked out and 5 types of experience such as sense, feel, think, act, relate of Bernd H. Schmitt was investigated. The spatial composition of drugstores were classified into destination, assortment, convenience and occasion, and through self experienced visual research, the experiential marketing strategy applied to drugstores and the elements of sales promotion applied with experiential marketing was analyzed. The streets of Hongik University as a strategic point of beauty, by selecting four H&B stores which were recently opened, a future direction is proposed by conducting the case analysis on the elements of sales promotion of drugstores and the spatial composition of drugstores applied with experiential marketing. In conclusion, in overall space, the behavioral experiential elements are weak. The behavioral experiential elements are a marketing that induce the intuitive behavior added with expertise and considered difficult to be maintained. Although the consumers think that the biggest value of drugstores is 'free and convenient product test' but in the other hand, they tend to think most positively about the consulting of experts. Therefore, the space emphasized with expertise should be more highlighted but such space should consider the convenience of consumers.

• Journal of the Korea Convergence Society
• /
• v.11 no.12
• /
• pp.125-130
• /
• 2020

The Korean maritime industry is growing rapidly as income levels rise. In particular, the domestic yacht market is generating steady market demand, which is a good opportunity for users who want to enjoy leisure. Among them, the experience-type yacht is operated smoothly around Suyeong Bay in Busan. In this study, a survey of experienced yacht users conducted an analysis focusing on color as much as the interior structure. The colors you experience when you stay in a specific space for a short time have a significant impact on the user's satisfaction and sensibility. Often, systematic research into space is often focused on physical distribution. However, color leaves a strong impression on short experiences as much information as it accepts through the optic nerve. A survey of yacht passengers was conducted to derive appropriate adjectives, and the results were obtained after analyzing them by means of I.R.I monochrome and image scale. Afterwards, it is expected that this research will be used as a theoretical basic data that can be used to carry out the production, repair, and repair of hands-on yachts that are developed on their own.

• Journal of Distribution Research
• /
• v.17 no.3
• /
• pp.115-132
• /
• 2012

This study empirically examines the impact of SSM market entry on changes in market shares among retailing types. The data is monthly time-series data spanning over the period from January 2000 to December 2010, and the effect of SSM market entry on market shares of retailing types is analyzed by utilizing several key factors such as the number of new SSM monthly entrants, total number of SSMs, the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. According to the Korean Standard Industrial Classification codes, the retailing type is classified into 5 groups: department stores, retail sale in other non-specialized large stores(big marts), supermarkets, convenience stores, and retail sale in other non-specialized stores with food or beverages predominating (others). The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. The empirical model controls for the size effects with the number of monthly employees for each retailing type and the macroeconomic effects with M2. The empirical model employed in this study is as follows; $$MS_i=f(NewSSM,\;CumSSM,\;employ_i,\;under165,\;M2)$$ where $MS_i$ is the market share of each retailing type (department stores, big marts), supermarkets, convenience stores, and others), NewSSM is the number of new SSM monthly entrants, CumSSM is total number of SSMs, $employ_i$ is the number of monthly employees for each retailing type, and under165 is the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. The correlation among these variables are reported in