• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Journal of Bio-Environment Control
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• v.24 no.2
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• pp.100-105
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• 2015

The calculation method of infiltration loss in greenhouse has different ideas in each design standard, so there is a big difference in each method according to the size of greenhouses, it is necessary to establish a more accurate method that can be applied to the domestic. In order to provide basic data for the formulation of the calculation method of greenhouse heating load, we measured the infiltration rates using the tracer gas method in plastic greenhouses equipped with various thermal curtains. And then the calculation methods of infiltration loss in greenhouses were reviewed. Infiltration rates of the multi-span and single-span greenhouses were measured in the range of $0.042{\sim}0.245h^{-1}$ and $0.056{\sim}0.336h^{-1}$ respectively, single-span greenhouses appeared to be slightly larger. Infiltration rate of the greenhouse has been shown to significantly decrease depending on the number of thermal curtain layers without separation of single-span and multi-span. As the temperature differences between indoor and outdoor increase, the infiltration rates tended to increase. In the range of low wind speed during the experiments, changes of infiltration rate according to the outdoor wind speed could not find a consistent trend. Infiltration rates for the greenhouse heating design need to present the values at the appropriate temperature difference between indoor and outdoor. The change in the infiltration rate according to the wind speed does not need to be considered because the maximum heating load is calculated at a low wind speed range. However the correction factors to increase slightly the maximum heating load including the overall heat transfer coefficient should be applied at the strong wind regions. After reviewing the calculation method of infiltration loss, a method of using the infiltration heat transfer coefficient and the greenhouse covering area was found to have a problem, a method of using the infiltration rate and the greenhouse volume was determined to be reasonable.

• Korean Journal of Agricultural Science
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• v.26 no.2
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• pp.77-93
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• 1999

This study is aiming at identifying the foreward and backward lingkage effects of the farm land base development project. Korean Government has continuously carried out farmland base development projets including the integrated agricultural development projects. large and medium scale irrigation projects and the comprehensive development of the four big river basin including tidal land reclamation and estuary dam construction for the all weather farming since 1962. the starting year of the five year economic development plans. Consequently the irrigation rate of paddy fields in Korea reached to 75% in 1998 and to escalate the irrigation rate, the Government had procured heavy investment fund from IBRD. IMF and OECF etc. To cope with the agricultural problems like trade liberalization in accordance with WTO policy, the government has tried to solve such problems as new farmland base development policy, preservation of the farmland and expansion of farmland to meet self-sufficiency of foods in the future. Especially, farmland base development projects have been challanged to environmental and ecological problems in evaluating economic benefits and costs where the value of non-market goods have not been included in those. Up to data, in evaluating benefits and costs of the projects, farmland base development projects have been confined to direct incremental value of farm products and it's related costs. Therefore the projects'efficiency as a decision making criteria has shown the low level of economic efficiencies. In estimating economic efficiencies including Leontiefs input-output analysis of the projects could not be founded in Korea at present. Accordingly this study is aimed at achieving and identifying the following objectives. (1) To identify the problems related to the financial supports of the Government in implementing the proposed projects. (2) To estimated backward and foreward linkage effects of the proposed project from the view point of national economy as a whole. To achieve the objectives, Hwangrak benefited area with reservoir which is located in Seosan-haemi Disticts, Chungnam Province were selected as a case study. The main results of the study are summarized as follows : a. The present value of investment and O & M cost were amounted to 3,510million won and the present value of the value added in related industries was estimated at 5.913million won for the period of economic life of 70 years. b. The total discounted value of farm products in the concerned industries derived by the project was estimated at 10,495million won and the foreward and backward linkage effects of the project were amounted to 6,760 and 5,126million won respectively. c. The total number of employment opportunities derived from the related industries for the period of project life were 3,136 man/year. d. Farmland base development projects were showed that the backward linkage effects estimated by index of the sensitivity dispersion were larger than the forward linkage effect estimated by index of the power of dispersion. On the other hand, the forward linkage effect of rice production value during project life was larger than the backward linkage effect e. The rate of creation of new job opportunity by means of implementing civil engineering works were shown high in itself rather than any other fields. and the linkage effects of production of the project investment were mainly derived from the metal and non-metal fields. f. According to the industrial linkage effect analysis, farmland base development projects were identified economically feasible from the view point of national economy as a whole even though the economic efficiencies of the project was outstandingly decreased owing to delaying construction period and increasing project costs.

• Management & Information Systems Review
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• v.33 no.4
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• pp.1-19
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• 2014

This Study focuses on the university students' job attitude and cost of employment preparation. Nowadays, many university and college students spend a big money improving their employment preparation such as studying on foreign language, getting various kinds of certificates and tooth correction, clothing etc. for employment interview. This study investigated the cost of employment preparation and Job attitude of the 484 students of universities and colleges, the analysis of the collected data was conducted with SPSS 12.0 program by using frequency analysis, factor analysis, reliability assessment, correlation test, t-test, one way ANOVA. The university students paid more costs of employment preparation such as a language training abroad, a private training, and clothing than the college students. Also, Allied social science students paid more costs of the language training abroad, and clothing than allied computer science and allied design students. The female students paid more money than male students for tooth correction. The costs of language training abroad, private training and clothing are affected the students' socioeconomic background of a home. Regarding the job attitude of students, the university students are feeling more positive than the college students of the employment efficacy and cognition of the education environment. As result, the differences in the cost of employment preparation by the university type, faculty major course, their sex, and socioeconomic background of a home. The student's employment-efficacy and cognition of the education environment are also differences between the university and the college students. So, to improve the job attitude, developing their ability for employment preparation, educational programs should be arranged in school and continuous researches are needed.

• Journal of Ecology and Environment
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• v.29 no.6
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• pp.593-602
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• 2006

Species composition, spatial distribution of major species, diameter and height classes distribution, and species diversity were .analyzed in the Korean red pine (Pinus densiflora, hereafter referred as pine) forest in the permanent quadrats, which were designed for Long Term Ecological Research (LTER). Collected data were compared with those from the other areas including urban center (Mt. Inwang and Hongneung) and boundary areas (Mts. Acha, Bukhan, Bulam, Cheonggye, Daemo, and Surak), and natural areas (Mts. Seolak, Songni, and Wolak) to clarify the ecological characteristics of pine forest on Mt. Nam. Species composition of pine forest on Mt. Nam showed a similarity with those of urban center but did a little and big differences with those on urban boundary and natural areas, respectively. Such differences that pine forest on Mt. Nam showed, were usually due to Styrax japonicus, Sorbus alnifolia, Oplismenus undulatifolius, Ailanthus altissima, Ageratina altissima and so on, which showed higher coverage there. Predicted from diameter and height classes distribution of tree species, pine forest on Mt. Nam showed a possibility to be replaced by a S. japonica. Considered that this replacer species is not only a sub-tree but also shade intolerant, such successional trend could be interpreted as a sort of retrogressive succession. Those on urban boundary and natural areas showed a difference by displaying probabilities to be maintained as themselves as an edaphic climax or succeeded to oak forests. Species diversity of pine forest on Mt. Nam was lower than those in urban boundary and natural areas due to excessive dominance of several species, which led to different species composition from the other areas. Plants, which produced the differences, were species that flourishes in the polluted industrial area (S. japonica and S. alnifolia), favors the disturbed site (O. undulatifolius), and exotic species (A. altissima and Eupatorium rugosum). Those results reflects that pine forest of Mt. Nam was exposed on severe environmental pollution and excessive human interferences.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.81-99
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• 2010

Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.34-47
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• 2009

Rapid urbanization is causing environmental and ecological damage, development thoughtless for the environment, and social and economical issues. It is important to grasp urban growth situations and characteristics, reflect them, and establish a policy for the solution of issues pursuant to urbanization and the sustainable and efficient development of national land. This research aims to be used as basic data in establishing an urban policy by analyzing the situations and characteristics of urban growth for the past 20 years in our entire country rather than an existing district. For this, some urban districts were sampled using a 1980s and 2000s version of land cover map produced by Ministry of Environment, and then pattern analysis for urban growth by administrative district ranks was conducted using GIS and a statistical technique. As a result, the development zone area after 1980s has increased by 2.5 times as compared to that before 1980s, and especially in the farm villages neighboring the national capital region, it has increased by 21.2 times. Special cities and metropolitan cities were developed at the districts being low in altitude, close to the principal road and the major downtown, high in road ratio, and restricted environmentally, ecologically and legally, and were diverted from mountains, forests and grassland to urban land. On the other hand, farm villages neighboring a large city, farm villages neighboring the national capital region, and local farm villages were developed at the districts being high in altitude, far from the principal road and the major downtown, low in road ratio, and not restricted environmentally, ecologically and legally, and were diverted from farmland to urban land. That is, it can be seen that urban development has been actively realized despite the unfavorable topographical conditions in the suburban districts due to lack of available land and various regulations and policies as urban growth around big cities expands.

• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.