• Korean Journal of Cognitive Science
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• v.35 no.2
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• pp.129-159
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• 2024

In the process of reading, readers can process information not only within the fixated region, known as the fovea, but also in the parafoveal region to the right of the fovea. While the parafoveal semantic preview effect has been confirmed in eye-tracking experiments using boundary techniques, research on how the parafoveal preview effects differ depending on the degree of semantic relatedness is still limited. This study investigates the parafoveal preview effects as a function of semantic relatedness with the target word. The experiment utilized Korean-Chinese bilinguals and presented mixed-language sentences as experimental stimuli. Four parafoveal preview conditions were applied to the target words in each sentence: (1) Korean identical condition, where the parafoveal word was the same as the target word (e.g., "나라," meaning "country" in English), (2) Chinese synonymous condition, where the parafoveal word had the same meaning as the target word (e.g., "国家," also meaning "country" in English), (3) Chinese semantically related condition, where the parafoveal word was semantically related to the target word (e.g., "政权," meaning "political power" in English), and (4) Chinese unrelated condition, where the parafoveal word was semantically unrelated to the target word (e.g., "围裙," meaning "apron" in English). The study explored the parafoveal preview effect in terms of the degree of semantic association with the target word. We found the most pronounced preview effect in conditions where the preview and the target word shared the same meaning, and we also observed preview effects in conditions where the semantic relatedness with the target word was relatively weak. This study suggests that the degree of semantic relatedness between the parafoveal preview word and the target word can influence readers' reading processes. It contributes to a better understanding of readers' eye movements and comprehension processes, with potential implications for the development of effective reading strategies and educational methods.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

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

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Journal of The Association for Neo Medicine
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• v.2 no.1
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• pp.35-54
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• 1997

We tried to observe the features of ancient medical practice by analysing the records related to medicine in the book, ${\ulcorner}$the Historical Records of the Three Kingdom${\lrcorner}$ of which content includes the features of medicine in mythology, plague, delivery of twins, drugs, medical system, shamanism, constitutional medicine, psychiatry, forensic medicine, deformity, a spa, medical phrase, health and welfare work, religion, death. physiological anatomy, Taoist medicine, acupuncture, the occult af of transformation and etc. Our initial concern was about where to draw line as of medical field and we defined medicine in more broad meaning. The book ${\ulcorner}$the Historical Records of the Three Kingdoms${\lrcorner}$ describes the world of mythology by way of medicine which is not clearly a conventional one. There appears records of birth of multiple offsprings 7 times in which cases are of triplets or more. Delivering multiple offsprings were rare phenomenon though such fertility was highly admired. This shows one aspect of ancient country having more population meant more power of the nation. Of those medical records conveyed in that book includes stories of childbirth such as giving birth to a son after praying, giving birth to Kim Yoo-shin after 20 months after mother's dream of conception, and a song longing for getting a laudable child. Plagues were prevalent throughout winter to spring season and one can observe various symptoms of plagues in the record. Of these epidemic diseases, cold type might have been more common than the heat one. Appearance of epidemic diseases frequently coincided with that of natural disasters that this suggests a linkage between plague and underlying doctrine on five elements' motion and six kinds of natural factors. There exists only a few names of diseases such as epidemic disease, wind disease, and syndrome characterized by dyspnea. Otherwise there appeared only afflictions that were not specified therefore it remains cluless to keep track of certain diseases of prevalence. Since this ${\ulcorner}$Historical Records of the Three Kingdoms'${\lrcorner}$ wasn't any sort of medical book, words and terms used were not technical kind and most were the ones used generally among lay people. Therefore any mechanisms of the diseases were hardly mentioned. Some of medicinal substances such as Calculus Bovis, Radix Ginseng, Gaboderma Luciderm, magnetitum were also in use in those days. 53 kinds of dietary supplies appears in the records and some of these might have been used as medicinal purpose. Records concerning dicipline of one's body includes activities such as hunting, archery, horseback riding etc. In Shilla dynasty there were positions such as professor of medicine, Naekongbong(內供奉), Kongbong's doctor(供奉醫師), Kongbong's diviner(供奉卜師). As an educational facility, medical school was built at the first year of King Hyoso's reign and it's curricula included various subjects as ${\ulcorner}$Shin Nong's Herbal classic${\lrcorner}$, ${\ulcorner}$Kabeul classic of acupuncture and moxbustion${\lrcorner}$, ${\ulcorner}$The Plain Questions of the Yellow Emperor's Classic of Internal Medicine${\lrcorner}$, ${\ulcorner}$Classic of Acupuncturer${\lrcorner}$, ${\ulcorner}$The Pulse Classic${\lrcorner}$, ${\ulcorner}$Classic of Channels and Acupuncture Points${\lrcorner}$ and ${\ulcorner}$Difficult Classic${\lrcorner}$. There were 2 medical professors who were in charge of education. To establish pharmacopoeia, 2 Shaji(舍知), 6 Sha(史), 2 Jongshaji(從舍知) were appointed. In Baekje dynasty, Department of Herb was maintained. Doing praying for the sake of health, doing phrenology also can be extended to medical arena. Those who survived over 100 years of age appear 3 times in the record, while 98 appears once. The earliest psychiatrist Nokjin differentiated symptoms to apply either therapies using acupuncture and drug or psychotherapy. There appears a case of rape, a case of burying alive with the dead, 8 cases of suicide that can characterize a prototype of forensic medicine. Deformity-related records include phrases as follow: 'there seems protrudent bone behind the head', 'a body which has two heads, two trunks, four arms.', 'a body equipped with two heads' In those times spa can be said to be used as a place for he리ing, convalescence, and relaxation seeing the records describing a person pretended illness and went to spa to enjoy with his friends. Priest doctors and millitary surgeons were in charge of the medical sevice in the period of the Three Kingdoms by the record written by Mookhoja(墨胡子) and Hoonkyeom(訓謙). Poor diet and regimen makes people more vulnerable to diseases. So there existed charity services for those poor people who couldn't live with one's own capacity such as single parents, orphans, the aged people no one to take care and those who are ill. The cause of affliction was frequently coined with human relation. There appeared the phenomenon of releasing prisoners and allowing people to become priests at the time of king's suffering. Besides, as a healing procedure, sutra-chanting was peformed. There appears 10 cases of death related records which varies from death by drowning, or by freezing, death from animals, death from war, death from wightloss and killing oneself at the moment of spouse's death and etc. There also exist certain records which suggest the knowledge of physiology and anatomy in those times. Since the taoist books such as ${\ulcorner}$Book of the Way and Its Power(老子道德經)${\lrcorner}$ were introduced in the period of Three Kingdoms, it can be considered that medicine was also influenced by taoism. Records of higher level of acupuncture, records which links the medicine and occult art of transformation existed. Although limited, we could figure out the medical state of ancient society.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.3
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• pp.20-35
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• 2022

This study was conducted on the locational results of the 'Yusanggoksu(流觴曲水)' petroglyphs located in Hwanggak-dong(黃閣洞), Shinsong-ri, Geumma-myeon, Iksan-si through literature study, analysis of old maps and aerial photos, field observations, drone photography, elevation surveys, and interviews with residents. It was attempted for the purpose of illuminating and preserving the relics of the domestic Yusanggoksu garden by clarifying the spatiality of this place by tracing the spatiality and examining the possibility of enjoying the Yusanggoksu water system in this place. The conclusion of this study is as follows. The area around Hwanggak-dong, where the Yusanggoksu remains, has been selected as the most beautiful scenic spot in Iksan in various documents. The origin of 'Hwanggak' is considered to be closely related to the nickname of Uijeongbu(議政府). In other words, he paid attention to the relationship with Yanggok, So Se-yang(蘇世讓), who served as Chan-seong Jwa(左贊成). In particular, he paid attention to the relationship with his birthplace, Taeheojeong, a separate book, and Toehyudang, a retreat hall), tombs, and posthumous Confucian academies were distributed in the vicinity. Haseo-dae(荷鋤臺), a wide rock on which a hoe is hung on a rock after field work, seems to express a leisurely rural life and a simple and hermit life, based on the examples of Chinese and Korean poetry. The dark blood on the upper part of the Seobwi Rock with the inscription 'Yusanggoksu', which is the core of this site, is identified as a chailgong(遮日孔) to support the water system, and Ilgan-pavilion and Mojeong(茅亭) nearby are to support the yusanggoksu. It seems to have performed a spatial function for The inscription 'Hwanggak-dong' engraved on the front of Deungzanbawi is the gateway to Hwanggakdongcheon(黃閣洞天) and identified the idealized world existing in the village. Judging from the documentary records of the Iksan-gun 『Chongswaelog(叢瑣錄)』, the rock letters 'Hwanggak-dong' and 'Haseodae' were engraved on March 29, 1901, the 5th year of Gwangmu, the 5th year of the Korean Empire, by Iksan-gun Governor Oh Haeng-mook(吳宖默) and his acquaintance Seokseong Kim In-gil(金寅吉) Confirmed. Also, considering the tense of Lee Bong-gu's 「Hwanggakdongun(黃閣洞韻)」 and So Jin-deok, a descendant of Yanggok, 「Hwanggakdongsihoe(黃閣洞詩會)」, it is presumed that it was related to Goksuyeon(曲水宴) in Hwanggak-dong. It can be inferred that the current affairs meetings were held at least until the early days of Japanese colonial rule. Meanwhile, the maximum width of the current curved waterway was calculated as 11.3m and the transverse slope was 15.0%. If so, it is estimated that the width and extension distance of the curved waterway would have been much longer. Judging from the use of mochun(暮春), drinking and poetry, the tense 'Hwanggakdongsihoe' related to the Yusanggoksu relics in Hwanggak-dong, and the existence of a pavilion presumed to be Yusangjeong(流觴亭) called Ilgan-pavilion in the nearby Yusanggoksu site It is confirmed that it was a space where Yusanggoksuyeon(流觴曲水宴) spread at least until the end of the Joseon Dynasty. Unfortunately, it remains a limitation of the study that it cannot be confirmed due to lack of data on the rock characters of 'Yusanggoksu' and those who enjoyed it before the end of the Joseon Dynasty. This is an area that needs to be elucidated through continuous efforts to find data on this issue in the future.

• Journal of Distribution Research
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• v.15 no.1
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• pp.1-24
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• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.