• The Korean Journal of Pharmacology
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• v.32 no.3
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• pp.323-334
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• 1996

Male Mongolian gerbils $(60{\sim}80g)$ were given DL-difluoromethylornithine (DFMO; 250mg/kg, ip) and methylglyoxal bis(guanylhydrazone) (MGBG; 50 mg/k, ip), respectively, 1 h prior to transient (7 min) occlusion of bilateral common carotid arteries (OBC7) and a daily dose of one of them for 6 days after recirculation, and the polyamine contents, activities of ornithine and S-adenosylmethionine decarboxylases (ODC and SAM-DC), and light microscopic findings of the hippocampus were evaluated. The hippocampal putrescine (PT) levels of the control gerbils treated with saline (STGr), markedly increased after OBC7, showing a peak level at 24 h after recirculation. The peak PT level was reduced in DFMO treated gerbils (DTCr) and in MGBG treated gerbils (MTGr). And 7 days after recirculation, the PT level of DTGr was decreased to about 75% of the PT level in the sham operated group (nonTGr) and to about 55% of the STGr level, respectively. The hippocampal spermidine (SD) level of STGr tended to decline, showing the lowest value at 8 h after recirculation. But the spermidine (SD) level of DTGr was somewhat higher at 8 h after OBC7 than those of STGr and MTGr The hippocampal spermine (SM) levels of all the experimental groups were little changed for 7 days after OBC. OBC7 markedly increased the hippocampal ODC activity. reaching a maximum (about 3 times higher than preischemic level) at 8 h and rapidly recovered to the control value by 24 h in STGr gerbils, and the OBC7-induced increase of ODC activity was significantly attenuated by DFMO or MGBG treatment. Whereas OBC7 induced a rapid decrease of the hippocampal SAMDC activity follwed by gradual recovery to the preischemic level, and the decrease of the SAMDC activity was slightly attenuated by DFMO or MGBG treatment. 7 Days after OBC7 the histological finding of the hippocampal complex stained with cresyl violet showed an extensive delayed neuronal damage in the CA1 region and to a lesser extent, in the dentate gyrus, sparing the CA3 region. And the neuronal death was aggevated by DFMO but significantly attenuated by MGBG. The immunochemical reactivity of hippocampus to anti-GFAP antibody was significantly increased in the CA1 region and to a lesser extent, in the dentate gyrus 7 days after OBC7, but was little changed in the CA3. And the increase of the anti-GFAP immunoreactivity was moderately enhanced by DFMO and significantly suppressed by MGBG. These results suggest that the polyamine metabolism may play a modulatory role in the ischemic brain damage.

• Journal of Hospice and Palliative Care
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• v.2 no.1
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• pp.23-35
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• 1999

Purpose : The hospice movement began about 30 years ago in Korea. However, basic studies have seldom been conducted about the general public's knowledge concerning hospice care and their needs for it. The purpose of this study was to investigate the general public's knowledge of and attitude toward hospice, and their needs for hospice care, and to analyze the needs for hospice care in relation to their knowledge and attitude in residents from a specific community. Methods : The survey was conducted with 924 people randomly selected from a district in Seoul. The data were collected through a self-reporting questionnaire constructed by the authors. With 30 items given in the questionnaire, the level of hospice needs showed Cronbach's alpha .89 in a pilot study and .92 in this study and the items were classified into four areas by a factor analysis. The data collected were analyzed by means of t-test and ANOVA. Results : 1) The average age of the respondents was 38. The majority of the respondents were well-educated. 2) Regarding awareness of hospice care, 54%(501 people) indicated they have heard of hospice. About 74% thought that people should be able to prepare for death in advance. About 83% wanted to be informed when they have life threatening illnesses such as terminal cancer. Also, about 63% responded that patients with terminal diseases should be provided with physical, spiritual, and psychological care for minimizing pain and peaceful death. Regarding the attitude toward hospice care, 74% responded that they would use hospice care if needed. The number of the respondents who preferred home visitation by the hospice team to care for the terminally ill ranked first with 34%. Concerning needs for hospice care : 1) By needs area, physical need showed highest mean(M=4.37), followed by social need(M=3.96), emotional need(M=3.87), and the spiritual need(M=3.79). The overall need level showed the mean value of 4.00 which reflects a considerable need for hospice care. 2) By demographic characteristics, people age over 50, the married, and the unemployed indicated higher level of needs for hospice care. Women showed higher level of needs than did men, and Catholics demonstrated higher level of needs than believers of other religion(P<0.0001). 3) As for the knowledge of and attitude toward hospice rare, the level of hospice care needs was significantly higher in the following groups: those who have heard of hospice, those who are aware of death preparation, those who want information on terminal diseases, those who want to use every method to sustain life, and those who are aware of hospice needs(P<0.001). Conclusion : It is assumed that the findings of this study on the knowledge, attitude, and needs for hospice care in the public can contribute to planning a successful hospice care program. Furthermore, the findings of this study will serve as useful data for the promotion of home hospice care to improve the quality of life of community residents, and contribute to the development of hospice care as a whole.

• Journal of Distribution Science
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• v.8 no.3
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• pp.27-35
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• 2010

As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.

• Asian Journal of Turfgrass Science
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• v.17 no.4
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• pp.129-146
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• 2003

Research was initiated to compare establishment vigor, uniformity, rooting potential and turf quality in sods of cool-season grasses (CSG). Several turfgrasses grown under pure sand soil were tested. Establishment vigor, uniformity, rooting potential and turf quality were evaluated in the study. Turfgrass entries were comprised of three blends from Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.), respectively and three mixtures among them. Differences by treatments were significantly observed in establishment vigor, uniformity, rooting potential and turf quality. Early establishment vigor was mainly influenced by germination speed, being fastest with PR, intermediate with TF and slowest with KB. In a late stage of growth, however, it was affected more by growth habit, resulting in highest with KB and slowest with TF. There were considerable variations in sod uniformity among turfgrasses. Best uniformity among monostand sods was associated with KB, while poorest one with TF. PR sod produced intermediate uniformity between KB and TF. The uniformity of polystand sods of CSG mixtures was inferior to that of monostands of KB, PR and TF, due to characteristics of mixtures comprised of a variety of color, density, texture and growth habit. The greatest potential of sod rooting was found with PR and the poorest with KB. Intermediate potential between PR and KB was associated with TF. In CSG mixtures, it was variable, depending on turfgrass mixing rates. Generally, the higher the PR in mixtures, the greater the sod rooting potential. At the time of sod harvest, however, turfgrass quality of KB was superior to that of PR. because of its characteristics of uniform surface, high density and good mowing quality. These results suggest that a careful expertise based on turf quality as well as sod characteristics like establishment vigor, uniformity and rooting potential be strongly required for the success of golf course or athletic field in establishment.

• Korean Journal of Psychosomatic Medicine
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• v.12 no.2
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• pp.157-164
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• 2004

Objectives : This study was designed to investigate depression, anxiety, alexithymia, stress responses between well-controlled and poorly-controlled diabetic patients by glycated hemoglobin levels. Methods : The subjects were 55 diabetic patients(mean age : $49.9{\pm}9.9$, 27 men and 28 women) who were confirmed to have diabetes depending on the laboratory findings as well as clinical symptoms at the St. Vincent Hospital Diabetes Clinic, from Mar. 2004 to Aug. 2004. Korean version of Beck Depression Inventory(BDI), State and Trait Anxiety Inventory(STAI), Toronto Alexithymia Scale(TAS) and Stress Response Inventory(SRI) were used for assessment. Based on glycated hemoglobin levels, the patients were divided into 10 well-controlled group(below 7%) and 45 poorly-controlled group(above 7%). We compared BDI, STAI, TAS and SRI scores between two groups by independent t-test. Results 1) Well-controlled diabetics, compared with poorly controlled group, manifested decreased illness duration($12.2{\pm}55.4$months vs. $55.4{\pm}66.6 months)(p=0.000), but other demographic data showed no difference between two groups. 2) The STAI scores of poorly-controlled group were significantly higher in both state anxiety sores $(38.7{\pm}3.8 \;vs.\;43.7{\pm}6.7)(p=0.29)$ and trait anxiety scores$(36.9{\pm}5.7\;vs.\;41.5{\pm}6.4)(p=0.43)$ than well-controlled groups. 3) No significant differences were found in the score of BDI, TAS, SRI between well and poorly-controlled diabetic groups. Conclusion : The above results suggest that poorly-controlled diabetic patients are more likely to have higher anxiety level than well-controlled diabetic patients. However, there were no differences in depression, alexithymia, stress responses between two group. We suggest that physicians should consider integrated approaches for psychiatric problems in the management of diabetic patients.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.18 no.3
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• pp.195-205
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• 1985

As a part of investigation to use the Anatrctic krill, Euphausia superba, more effectively as a food source, processing conditions, utilizations and storage stability of krill paste (intermediate product of krill) were examined and also chemical compositions of krill paste were analyzed. Frozen raw krill was chopped, agitated with $25\%$ of water to the minced krill and then centrifuged to separate the liquid fraction from the residue. This liquid fraction was heated at $98^{\circ}C$ for 20 min. to coagulate the proteins of krill, and it was filtered to separate the protein fraction. Krill paste was prepared with grinding the protein fraction, adding $0.2\%$ of polyphosphate and $0.3\%$ of sodium erythorbate to the krill paste for enhancing of functional properties and quality stability. The krill paste was packed in a carton box, and then stored at $-30^{\circ}C$. Chemical compositions of krill paste were as follows : moisture $78\%$, crude protein $12.9\%$, crude lipid $5.9\%$, and the contents of hazardous elements of krill paste as Hg 0.001 ppm, Cd 1.15 ppm, Zn 9.1 ppm, Pb 0.63 ppm and Cu 11.38ppm were safe for food. The amino acid compositions of krill paste showed relatively high amount of taurine, glutamic acid, aspartic acid, leucine, lysine and arginine, which occupied $55\%$ of total amino acid and also taurine, lysine, glycine, arginine and proline were occupied $65\%$ of total free amino acid. Fatty acid compositions of krill paste consist of $32.4\%$ of saturated fatty acid, $29.6\%$ of monoenoic acid and $38.0\%$ of polyenoic acid, and major fatty acids of product were eicosapentaenoic acid ($17.8\%$), oleic acid ($16.9\%$), palmitic acid ($15.3\%$), myristic acid ($8.7\%$) and docosahexaenoic acid ($8.4\%$). In case of procssing of fish sausage as one of experiment for krill paste use, Alaska pollack fish meat paste could be substituted with the krill paste up to $30\%$ without any significant defect in taste and texture of fish sausage, and the color of fish sausage could be maintained by the color of krill paste. Judging from the results of chemical and microbial experiments during frozen storage, the quality of krill paste could be preserved in good condition for 100 days at $-39^{\circ}C$.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.20 no.1
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• pp.41-51
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• 1987

This study was carried out to prepare powdered smoked-dried mackerel which can be used as a soup base, and to examine storage stability and the taste compounds of Products. Raw mackerel are filleted, toiled for 10 minutes and pressed to remove lipids, and then soaked in extract solution of skipjack meat. This soaked mackerel are smoked 3 times to $10-12\%$ moisture content at $80^{\circ}C$ for 8 hours. And the smoked-dried mackerel were pulverized to 50 mesh. Finally, the powdered smoked-dried mackerel were packed in a laminated film $bag(PET/Al\;foil/CPP:\;5{\mu}m/15{\mu}m/70{\mu}m,\;15\times17cm)$ with air(product C), nitrogen(product N) and oxygen absorber(product O), and then stored at room temperature for 100 days. The moisture and crude lipid content of powdered smoked-dried mackerel was $11.3-12.3\%,\;12\%$, respectively, and water activity is 0.52-0.56. And these values showed little changes during storage. The pH, VBN and amino nitrogen content increased slowly during storage. Hydrophilic and lipophilic brown pigment formation showed a tendency of increase in product(C) and showed little change in product(N) and (O). The TBA value, peroxide value and carbonyl value of product(N) and (O) were lower than those of product (C). The major fatty acids of products were 16:0, 18:1, 22:6, 18:0 and 20:5, and polyenoic acids decreased, while saturated and monoenoic acids increased during processing and storage of products. The IMP content in products were 420.2-454.2 mg/100 g and decreased slightly with storage period. And major non-volatile organic acids in products were lactic acid, succinic acid and $\alpha-ketoglutaric$ acid. In free amino acids and related compounds, major ones are histidine, alanine, hydroxyproline, lysine, glutamic acid and anserine, which occupied $80.8\%$ of total free amino acids. The taste compounds of powdered smoked-dried mackerel were free amino acids and related compounds (1,279.4 mg/100 g), non-volatile organic acids(948.1 mg/100 g), nucleotides and their related compounds (672.8 mg/100 g), total creatinine(430.4 ntg/100 g), tetaine(86.6 mg/100 g) and small amount of TMAO. The extraction condition of powdered smoked-dried mackerel in preparing soup stock is appropriate at $100^{\circ}C$ for 1 minute. Judging from the results of taste and sensory evaluation, it is concluded that the powdered smoked-dried mackerel can be used as natural flavoring substance in preparing soups and broth.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• 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.26 no.1
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• pp.1-21
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• 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.