• KOREAN JOURNAL OF CROP SCIENCE
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• v.17
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• pp.115-133
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• 1974

This study was done on the metabolism of chemical components during the seed development of ginseng. The changes of the chemical components were inspected in the following periods: from the early stage of flower organ formation to flowering time, from the early stage of fruiting to maturity, during the moisture stratification before sowing. From flower bud forming stage to meiosis stage, the changes in the fresh weight, dry weight, contents of carbohydrates, and contents of nitrogen compounds were slight while the content of TCA soluble phosphorus and especially the content of organic phosphorus increased markedly. From meiosis stage to microspore stage the fresh and dry weights increase greatly. Also, the total nitrogen content increases in this period. Insolub]e nitrogen was 62-70% of the total nitrogen content; the increase of insoluble nitrogen seems to have resulted form the synthesis of protein. The content of soluble sugar (reducing and non-reducing sugar) increases greatly but there was no observable increase in starch content. In this same period, TCA soluble phosphorus reached the maximum level of 85.4% of the total phosphorus. TCA insoluble phosphorus remained at the minimum content level of 14.6%. After the pollen maturation stage and during the flowering period the dry weight increased markedly and insolub]e nitrogen also increased to the level of 67% of the total nitrogen content. Also in this stage, the organic phosphorus content decreased and was found in lesser amounts than inorganic phosphorus. A rapid increase in the starch content was also observed at this stage. In the first three weeks after fruiting the ginseng fruit grows rapidly. Ninety percent of the fresh weight of ripened ginseng seed is obtained in this period. Also, total nitrogen content increased by seven times. As the fruits ripened, insoluble nitrogen increased from 65% of the total nitrogen to 80% while soluble nitrogen decreased from 35% to 20%. By the beginning of the red-ripening period, the total phosphoric acid content increased by eight times and was at its peak. In this same period, TCA soluble phosphorus was 90% of total phosphorus content and organic phosphorus had increased by 29 times. Lipid-phosphorus, nucleic acid-phosphorus and protein-phosphorus also increased during this stage. The rate of increase in carbohydrates was similar to the rate of increase in fresh weight and it was observed at its highest point three weeks after fruiting. Soluble sugar content was also highest at this time; it begins to decrease after the first three weeks. At the red-ripening stage, soluble sugar content increased again slightly, but never reached its previous level. The level of crude starch increased gradually reaching its height, 2.36% of total dry weight, a week before red-ripening, but compared with the content level of other soluble sugars crude starch content was always low. When the seeds ripened completely, more than 80% of the soluble sugar was non-reducing sugar, indicating that sucrose is the main reserve material of carbohydrates in ginseng seeds. Since endosperm of the ripened ginseng seeds contain more than 60% lipids, lipids can be said to be the most abundant reserve material in ginseng seeds; they are more abundant than carbohydrates, protein, or any other component. During the moisture stratification, ginseng seeds absorb quantities of water. Lipids, protein and starch stored in the seeds become soluble by hydrolysis and the contents of sugar, inorganic phosphorus, phospho-lipid, nucleic acid-phosphorus, protein phosphorus, and soluble nitrogen increase. By sowing time, the middle of November, embryo of the seeds grows to 4.2-4.7mm and the water content of the seeds amounts to 50-60% of the total seed weight. Also, by this time, much budding material has been accumulated. On the other hand, dry stored ginseng seeds undergo some changes. The water content of the seeds decreases to 5% and there is an observable change in the carbohydraes but the content of lipid and nitrogen compounds did not change as much as carbohydrates.

• Journal of Distribution Research
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• v.17 no.3
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• pp.25-57
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• 2012

This study identified motives for writing apparel product reviews in online stores, and determined what motives increase the behavior of writing reviews. It also classified store customers based on the type of writing motives, and clarified the characteristics of internet purchase behavior and of a demographic profile. Data were collected from 252 females aged 20s' and 30s' who have experience of reading and writing reviews on online shopping. The five types of writing motives were altruistic information sharing, remedying of a grievance and vengeance, economic incentives, helping new product development, and the expression of satisfaction feelings. Among five motives, altruistic information sharing, economic incentives, and helping new product development stimulate writing reviews. Store customers who write reviews were classified into three groups based on their writing motive types: Other consumer advocates(29.8%), self-interested shoppers(40.5%) and shoppers with moderate motives(29.8%). There were significant differences among three groups in writing behavior (the frequency of writing reviews, writing intent of reviews, duration of writing reviews, and frequency of online shopping) and age. Based on results, managerial implications were suggested. Long Abstract : The purpose of present study is to identify the types of writing motives on online shopping, and to clarify the motives affecting the behavior of writing reviews. This study also classifies online shoppers based on the motive types, and identifies the characteristics of the classified groups in terms of writing behavior, frequency of online shopping, and demographics. Use and Gratification Theory was adopted in this study. Qualitative research (focus group interview) and quantitative research were used. Korean women(20 to 39 years old) who reported experience with purchasing clothing online, and reading and writing reviews were selected as samples(n=252). Most of the respondents were relatively young (20-34yrs., 86.1%,), single (61.1%), employed(61.1%) and residents living in big cities(50.9%). About 69.8% of respondents read and 40.5% write apparel reviews frequently or very frequently. 24.6% of the respondents indicated an "average" in their writing frequency. Based on the qualitative result of focus group interviews and previous studies on motives for online community activities, measurement items of motives for writing after-purchase reviews were developed. All items were used a five-point Likert scale with endpoints 1 (strongly disagree) and 5 (strongly agree). The degree of writing behavior was measured by items concerning experience of writing reviews, frequency of writing reviews, amount of writing reviews, and intention of writing reviews. A five-point scale(strongly disagree-strongly agree) was employed. SPSS 18.0 was used for exploratory factor analysis, K-means cluster analysis, one-way ANOVA(Scheffe test) and ${\chi}^2$-test. Confirmatory factor analysis and path model analysis were conducted by AMOS 18.0. By conducting principal components factor analysis (varimax rotation, extracting factors with eigenvalues above 1.0) on the measurement items, five factors were identified: Altruistic information sharing, remedying of a grievance and vengeance, economic incentives, helping new product development, and expression of satisfaction feelings(see Table 1). The measurement model including these final items was analyzed by confirmatory factor analysis. The measurement model had good fit indices(GFI=.918, AGFI=.884, RMR=.070, RMSEA=.054, TLI=.941) except for the probability value associated with the ${\chi}^2$ test(${\chi}^2$=189.078, df=109, p=.00). Convergent validities of all variables were confirmed using composite reliability. All SMC values were found to be lower than AVEs confirming discriminant validity. The path model's goodness-of-fit was greater than the recommended limits based on several indices(GFI=.905, AGFI=.872, RMR=.070, RMSEA=.052, TLI=.935; ${\chi}^2$=260.433, df=155, p=.00). Table 2 shows that motives of altruistic information sharing, economic incentives and helping new product development significantly increased the degree of writing product reviews of online shopping. In particular, the effect of altruistic information sharing and pursuit of economic incentives on the behavior of writing reviews were larger than the effect of helping new product development. As shown in table 3, online store shoppers were classified into three groups: Other consumer advocates (29.8%), self-interested shoppers (40.5%), and moderate shoppers (29.8%). There were significant differences among the three groups in the degree of writing reviews (experience of writing reviews, frequency of writing reviews, amount of writing reviews, intention of writing reviews, and duration of writing reviews, frequency of online shopping) and age. For five aspects of writing behavior, the group of other consumer advocates who is mainly comprised of 20s had higher scores than the other two groups. There were not any significant differences between self-interested group and moderate group regarding writing behavior and demographics.

• Korean Journal of Weed Science
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• v.16 no.4
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• pp.264-281
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• 1996

As a consequence of wide use of herbicides, Eleocharis kuroguwai Ohwi became a dorminant problem weed for rice cultivation in Korea. To understand the establishment of the weed, experiments on physio-ecological characteristics were carried out sprouting and occurrence, the results could be summarized as follows: Sprouting percentage remained 68 to 73% until the time of field emergence, indicating many of the them are still dormant. The proportion of the dormant tubers were greater for the smaller than the bigger tubers. Apical dominance was apparent in sprouting, with 84% of tuber sprouted from only one of the apical buds. Tubers sprouted from 2 or 3 buds were less than 20%, and were mostly from the bigger tubers. When the shoot growth was compared, by controlling the others, ones from apical and the next 3 buds showed similar vigorous growth, but the later ones showed poorer growth. For the longevity of tubers, deep soil storage appeared to be better than storage in temperature controlled room to 2~$3^{\circ}C$. Emergence of E. kuroguwai was better in clay soil than in sand, and the possible depth for emergence in clay soil appeared to be up to 21cm, but was 15cm in sand. When tubers were exposed to salt solutions before emergence tests, E. kuroguwai appeared to be much sensitive to salts than S.planiculmis. Among the tubers formed in previous year, 12.7% remained still viable until the end of next crop season, but with relatively strong dormancy. The first emergence was about 10 days after planting at ordinary cropping seasons, and the days to the maximum shoot number stage were 60~90 from planting. The duration was extended at early transplanting, and shoot number, leaves per shoot, and tubers developed per plant were also greater at early plantings. The 6th order offshoots were developing when E. kuroguwai was planted at early season. When planted at later seasons, generation and the number of offshoots was reduced planted at early season. When planted at later seasons, generation and the number of offshoots was reduced and the number of tubers, runner and rhizome lengths was also reduced.

• Journal of Distribution Science
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• v.10 no.4
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• pp.13-20
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• 2012

The "flextime" system, which was initially designed to maintain a balance between work and personal life, has recently received much attention as an alternative form of work, enabling employees to fully exert their creativity. Most studies show that the effects of flextime on performance, productivity, attitude toward the organization, absenteeism, and turnover differ between managerial and non-managerial workers. This suggests that workers' personal characteristics affect their preference for flextime by directly or indirectly influencing its result variables. As most Korean companies have not adopted the flextime system, little research has been conducted on it in Korea. Recently, Korean companies have been discussing flextime as one of several measures for enhancing international competitiveness. Therefore, this study aims to offer a theoretical framework for the introduction of the system by analyzing the effects of the precedent factors on the preference for flextime. Though not statistically significant, a higher preference for flextime is noted among workers over the age of 36. Older workers usually are more conservative and less adaptable to change but here the older Korean workers may be anxious and resistant. Additional research on workers in different types of businesses using improved research methods will lead to more meaningful results. Married workers display a lower preference to flextime than single workers. In Korea, the current atmosphere focused on a happy home encourages married workers to prefer regular work hours, enabling them to go to and from work on a regular schedule. This means that normal working hours, from morning to evening, are preferred as it is the most suitable system for families. However, this is not so in the case of single workers. Unmarried singles tend to prefer flextime for investing in self-development toward future prosperity, over the benefits of regular working-hours. Flextime is designed to meet their needs to some extent as it is helpful in maintaining a balance between work life and self-development. If flextime is selected, workers can spend mornings on self-development and work in the afternoons. Therefore, when flextime is introduced in Korea, it would be desirable to start with unmarried workers, to increase corporate creativity and productivity and develop individual potential. In particular, when the five-day workweek, the main concern for companies and labor unions, is adopted, synergy with flextime could be expected and a gradual implementation of flextime will be effective. Gender difference shows similar results to marital status with male workers displaying a higher preference for flextime. It is inferred that male workers' attitudes toward flextime are more favorable than female workers' because flextime enables self-development and work life to coexist. A relatively weak, though statistically significant, correlation exists between control position and flextime preference with inner-control-oriented workers displaying favorable attitudes toward flextime. Generally, inner-control-oriented workers tend to attribute the consequences caused by any person or partner relationship to themselves. Thus, when a new system is introduced they are likely to have less reluctance and fear than outer-control-oriented workers, because they think it is important to deal with the new system. A weak but slight correlation exists between the desire for achievement and flextime preference. People who have a higher desire for achievement are willing to consider the new system, especially if significant success is reasonably expected. This result is derived from a reasonable judgment that flextime offers an individual the time for self-development while the organization benefits from the resulting creativity and performance enhancements. Although not the primary analysis, a high correlation is found between control position and the desire for achievement, which is consistent with the results of previous research. The regression analysis not only supports the preceding ANOVA and correlation analysis but also shows the existence of a causal relationship. Married workers have a weak preference for flextime, which is consistent with the results of the preceding ANOVA. Relative to men, women have a weak preference for flextime. No statistically significant correlation was noticed for age. Inner-control-oriented workers prefer flextime more than outer-control-oriented workers as the former view the consequences of change to be their own responsibility. However, the preference for flextime seems to be weak. As expected, people with a higher desire for achievement have a stronger preference for flextime, presumably because the greater the desire for achievement, the stronger the spirit of challenging an uncertain future. No significant correlation exists between job satisfaction and flextime preference.

• Journal of Korean Society of Forest Science
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• v.36 no.1
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• pp.9-25
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• 1977

As a successive work of the variation studies of natural Pinus densiflora stands, some characteristics of individual trees of the three natural populations selected from the Kwang-won Province, the middle-east part of Korean peninsula, as shown in the location map, were investigated. And the statiscal differences between individuals within population, and between populations were analysed. Twenty trees from each population were selected for this study purpose. Doing this, those trees lagged in growth, usually showing poorer form, were eliminated. The results obtained are summarized as follows: 1. Though the average population ages had the ranage between 50 and 63, the growth of height or diameter was similar. Population No.9 is, however, considered to have better tree forms at glance. Population No.8 showed the heighest value not only in the clear-stem-length ratio. 0.53 but also in the crown-index 0.91. The higher value can be result from those trees having long lateral branches and relatively short crown height, meaning undesirable crown shape. In regard to the fine branchedness and the acuteness of branching angle, the population No.9. is considered to be a better one, whereas there was almost no difference in crown height among populations. 2. Checking the frequency distributions of the ratio of the clear-stem-height to the total height and the crown-indices, some difference between populations are considered. These might be attributed to the previous way of stand mangement which alters the density. 3. In the serration density, the average number of 54 per 1cm needle length, the significant differences exist between individual trees within population but not between populations. A few trees which extremly high serration density were observed. As in serration, so tendencies were in the number of stomata row and resin duct. 4. The population 8 had the resin duct index value of 0.074 as the highest which was twice or triple of the other ones. 5. The patterns of increasing process of the average 10-year-ring-segment were not similar till the 30 years of age, but beyond this, the tendency lines were aggregated. 6. Regading the average summer wood ratio, no diffrence between populations, but in the ranges, i.e. 23 to 30 in population No.8. and 16 to 36 in population No.9., with regad to the specific gravity of wood, there were hardly observed any difference between populations even in the ranges values. As the increase of tree ages, the increase of specific gravity was followed but the increasing patterns were not similar between populations. 7. No significant differences between populations in the average tracheid length and the range were detected. However, the length was increased according to the age increase. The increasing pattern was same between populations.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.916-924
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• 1996

Bacground : Percutaneous needle aspiration biopsy (PCNA) is one of the most frequently used diagnostic methcxJs for intrathoracic lesions. Previous studies have reponed wide range of diagnostic yield from 28 to 98%. However, diagnostic yield has been increased by accumulation of experience, improvement of needle and the image guiding systems. We analysed the results of PCNA performed for one year to evaluate the diagnostic yield, the rate and severity of complications and factors affecting the diagnostic yield. Method : 287 PCNAs undergone in 236 patients from January, 1994 to December, 1994 were analysed retrospectively. The intrathoracic lesions was targeted and aspirated with 21 - 23 G Chiba needle under fluoroscopic guiding system. Occasionally, 19 - 20 G Biopsy gun was used for core tissue specimen. The specimen was requested for microbiologic, cytologic and histopathologic examination in the case of obtained core tissue. Diagnostic yields and complication rate of benign and malignant lesions were ca1culaled based on patients' chans. The comparison for the diagnostic yields according to size and shape of the lesions was analysed with chi square test (p<0.05). Results : There are 19.9% of consolidative lesion and 80.1% of nodular or mass lesion, and the lesion is located at the right upper lobe in 26.3% of cases, the right middle lobe in 6.4%, the right lower lobe 21.2%, the left upper lobe in 16.8%, the left lower lobe in 10.6%, and mediastinum in 1.3%. The lesion distributed over 2 lobes is as many as 17.4% of cases. There are 74 patients with benign lesions, 142 patients with malignant lesions in final diagnosis and confirmative diagnosis was not made in 22 patients despite of all available diagnostic methods. 2 patients have lung cancer and pulmonary tuberculosis concomittantly. Experience with 236 patients showed that PCNA can diagnose benign lesions in 62.2% (42 patients) of patients with such lesions and malignant lesions in 82.4% (117 patients) of patients. For the patients in whom the first PCNA failed to make diagnosis, the procedure was repeated and the cumulative diagnostic yield was increased as 44.6%, 60.8%, 62.2% in benign lesions and as 73.4%, 81.7%, 82.4% in malignant lesions through serial PCNA. Thoracotomy was performed in 9 patients with benign lesions and in 43 patients with malignant lesions. PCNA and thoracotomy showed the same pathologic result in 44.4% (4 patients) of benign lesions and 58.1% (25 patients) of malignant lesions. Thoracotomy confirmed 4 patients with malignat lesions against benign result of PCNA and 2 patients with benign lesions against malignant result of PCNA. There are 1.0% (3 cases) of hemoptysis, 19.2% (55 cases) of blood tinged sputum, 12.5% (36 cases) of pneumothorax and 1.0% (3 cases) of fever through 287 times of PCNA. Hemoptysis and blood tinged sputum didn't need therapy. 8 cases of pneumothorax needed insertion of classical chest tube or pig-tail catheter. Fever subsided within 48 hours in all cases. There was no difference between size and shape of lesion with diagnostic yield. Conclusion: PCNA shows relatively high diagnostic yield and mild degree complications but the accuracy of histologic diagnosis has to be improved.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.