• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.19-25
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• 2023

This study aimed to analyze the current status of planted trees in Seoul Forest and propose improvement plans to improve the naturalness in the park. A comprehensive survey of the trees in the park was conducted, and the data gathered was used to build a list of planting trees suitable for an urban park. The analysis of the characteristics of landscape trees in Seoul Forest by type was about the presence or absence of leaves, and they were classified into deciduous trees, evergreen trees, deciduous shrubs, and evergreen shrubs, and herbaceous plants such as groundcover plants separately classified. The study found that Seoul Forest had 57 species of native and naturalized trees, with 27 deciduous trees, 35 deciduous shrubs, 15 evergreen trees, and 98 evergreen shrubs. The park also had 472 species of herbaceous plants, totaling 320,000. The majority of planted trees in Seoul Forest were native species, comprising 59% of the total planted trees, while naturalized species made up 41%. Furthermore, the ratio of deciduous trees to evergreen trees was 81% to 19%, with deciduous trees being the dominant species. The evergreen trees showed a similar trend, with a total of 23 species, including 15 native and 8 foreign species, accounting for 65% of native species. In addition, the study identified six common deciduous shrubs, including Forsythia koreana, orbaria sorbifolia var. stellipila, Deutzia parviflora, Rhododendron lateritium, and Spiraea prunifolia var. simpliciflora, which are frequently planted in areas with abundant water. The study also revealed that among the 10 evergreen shrub species, 9 were native and 1 was foreign. The study aimed to classify the species planted in Seoul Forest into native and foreign species and to provide a data-driven plan to encourage the planting of native species. This study offers valuable insights into planting planning and design for urban parks, which is essential for enhancing naturalness, as most studies have primarily focused on usage patterns and satisfaction in urban parks. By promoting the planting of native species, the naturalness of Seoul Forest can be improved.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.47-66
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• 2023

The purpose of this study was to develop an educational smart app for classes by reconstructing some of the teaching-learning contents of the clothing preparation planning within the 'clothing preparation planning and selection' curriculum unit. To this end, a teaching-learning process plan was planned for the classes, a smart app was developed for classes, and feedback from home economics teachers and app development experts was received for the developed app. The main composition of the developed app consists of five steps. The first step is to set up a profile using a real photo, ZEPETO or Galaxy emoji, or iPhone Memoji. In the second step, students make a list of clothes by figuring out the types, quantities and conditions of their exisitng wardrobe items. Each piece of clothing is assigned an individual registration number, and stduents can take pictures of the front and back, along with describing key attributes such as type, color, season-appropriateness, purchase date, and current status. Step three guides students in deciding which garments to retain and which to discard. Building on the clothing inventory from the previous step, students classify items to keep and items to dispose of. In Step 4, Deciding How to Arrange Clothing, students decide how to arrange clothing by filling out an alternative scorecard. Through this process, students can learn in advance the subsection of resource management and self-reliance, laying the foundationa for future learning in 'Practice of Rational Consumption Life'. Lastly, in the fifth stage of determining the disposal method, this stage is to develop practical problem-oriented classes on how to dispose of the clothes to be discarded in the thirrd stage by exploring various disposal methods, engaging in group discussions, and sharing opinions. This study is meaningful as a case study as an attempt to develop a smart app for education by an instructor to align teaching plans and educational content with achievement standards for the class. In the future, upgrades will have to be made through user application.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.4
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• pp.58-67
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• 2020

The present study was conducted as part of basic research for selecting species of street trees with historical value in Seoul. It also made up a list of traditional landscape trees for a variety of alternatives. The following results are shown below. As to the history of street trees in Korea, records on to-be-estimated street trees are found in historical documents written in King Yangwon during the second year of Goguryeo Dynasty (546) and King Myeongjong during 27 year of Goryeo (1197). However, it is assumed that lack of clarity is found in historical records. During the 23 year of King Sejong in the early Joseon Dynasty (1441), the record showed that the state planted street trees as guideposts on the postal road. The records revealed that Ulmus spp. and Salix spp. were planted as guidance trees. The street tree system was performed in the early Joseon Dynasty as recorded in the first year of King Danjong document. Pinus densiflora, Pinus koraiensis, Pyrus pyrifolia var. culta, Castanea crenata, Styphnolobium japonicum and Salix spp. were planted along the avenue at both left and right sides. Morus alba were planted on streets during the five year of King Sejo (1459). As illustrated in pieces Apgujeong by painter Jeongseon and Jinheonmajeongsaekdo in the reign of King Yeongjo, street trees were planted. This arrangement is associated with a number of elements such as king procession, major entrance roads in Seoul, place for horse markets, prevention of roads from flood and indication. In the reign of King Jeongjo, there are many cases related to planting Pinus densiflora, Abies holophylla and Salix spp. for king procession. Turning king roads and related areas into sanctuaries is considered as technique for planting street trees. During the 32 year of King Gojong after opening ports (1985), the state promoted planting trees along both sides of roads. At the time, many Populus davidiana called white poplars were planted as rapidly growing street trees. There are 17 taxa in the Era of Three Kingdoms records, 31 taxa in Goryeo Dynasty records and 55 taxa in Joseon Dynasty records, respectively, described in historical documents to be available for being planted as street trees in Seoul. 16 taxa are recorded in three periods, which are Era of Three Kingdoms, Goryeo Dynasty and Joseon Dynasty. These taxa can be seen as relatively excellent ones in terms of historical value. The introduction of alien plants and legal improvement in the Japanese colonial period resulted in modernization of street tree planting system. Under the six-year street tree planting plan (1934-1940) implemented as part of expanding metropolitan areas outside the capital launched in 1936, four major street trees of top 10 taxa were a Populus deltoides, Populus nigra var. italica, Populus davidiana, Populus alba. The remaining six trees were Salix babylonica, Robinia pseudoacacia, platanus orientalis, Platanus occidentalis, Ginkgo biloba, and Acer negundo. Beginning in the mid- and late 1930s, platanus orientalis, Platanus occidentalis were introduced into Korea as new taxa of street trees and planted in many regions. Beginning on 1942, Ailanthus altissima was recommended as street trees for the purpose of producing silks. In 1957 after liberation, major street tree taxa included Platanus occidentalis, Ginkgo biloba, Populus nigra var. italica, Ailanthus altissima, Populus deltoides and Salix babylonica. The rank of major street tree species planted in the Japanese colonial period had changed. Tree planting trend around that period primarily representing Platanus occidentalis and Ginkgo biloba still holds true until now.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• MISULJARYO - National Museum of Korea Art Journal
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• v.97
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• pp.87-104
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• 2020

Myogilsang on Diamond Mountain, signed and dated (2000) by Seon-u Yeong (1946-2009), is the first work by a North Korean artist to enter the collection of the National Museum of Korea (fig. 1a). The donor acquired the painting directly from the artist in Pyeongyang in 2006. In consequence, there are no issues with the painting's authenticity.This painting is the largest among all existing Korean paintings, whether contemporary or from the Joseon Dynasty, to depict this iconography (see chart 1. A Chronological List of Korean Myogilsang Paintings.) It is ink and color on paper, measures 130.2 × 56.2 centimeters, and is in a hanging scroll format. Since this essay is intended as a brief introduction of the painting and not in-depth research into it, I will simply examine the following four areas: 1. Seon-u Yeong's background; 2. The location and the traditional appellation of the rock-cut image known as Myogilsang; 3. The iconography of the image; and 4) A comparative analysis of Seon-u Yeong's painting in light of other paintings on the same theme. Finally, I will present two more of his works to broaden the understanding of Seon-u Yeong as a painter. 1. Seon-u Yeong: According to the donor, who met Seon-u at his workshop in the Cheollima Jejakso (Flying Horse Workshop) three years before the artist's death, he was an individual of few words but displayed a firm commitment to art. His preference for subjects such as Korean landscapes rather than motifs of socialist realism such as revolutionary leaders is demonstrated by the fact that, relative to his North Korean contemporaries, he seems to have produced more paintings of the former. In recent years, Seon-u Yeong has been well publicized in Korea through three special exhibitions (2012 through 2019). He graduated from Pyeongyang College of Fine Arts in 1969 and joined the Central Fine Arts Production Workshop focusing on oil painting. In 1973 he entered the Joseon Painting Production Workshop and began creating traditional Korean paintings in ink and color. His paintings are characterized by intense colors and fine details. The fact that his mother was an accomplished embroidery specialist may have influenced on Seon-u's choice to use intense colors in his paintings. By 1992, he had become a painter representing the Democratic People's Republic of Korea with several titles such as Artist of Merit, People's Artist, and more. About 60 of his paintings have been designated as National Treasures of the DPRK. 2. The Myogilsang rock-cut image is located in the Manpok-dong Valley in the inner Geumgangsan Mountain area. It is a high-relief image about 15 meters tall cut into a niche under 40 meters of a rock cliff. It is the largest of all the rock-cut images of the Goryeo period. This image is often known as "Mahayeon Myogilsang," Mahayeon (Mahayana) being the name of a small temple deep in the Manpokdong Valley (See fig. 3a & 3b). On the right side of the image, there is an intaglio inscription of three Chinese characters by the famous scholar-official and calligrapher Yun Sa-guk (1728-1709) reading "妙吉祥"myogilsang (fig. 4a, 4b). 3. The iconography: "Myogilsang" is another name for the Bhodhisattva Mañjuśrī. The Chinese pronunciation of Myogilsang is "miaojixiang," which is similar in pronunciation to Mañjuśrī. Therefore, we can suggest a 妙吉祥 ↔ Mañjuśrī formula for the translation and transliteration of the term. Even though the image was given a traditional name, the mudra presented by the two hands in the image calls for a closer examination. They show the making of a circle by joining the thumb with the ring finger (fig. 6). If the left land pointed downward, this mudra would conventionally be considered "lower class: lower life," one of the nine mudras of the Amitabha. However, in this image the left hand is placed across its abdomen at an almost 90-degree angle to the right hand (fig. 6). This can be interpreted as a combination of the "fear not" and the "preaching" mudras (see note 10, D. Saunders). I was also advised by the noted Buddhist art specialist Professor Kim Jeong-heui (of Won'gwang University) to presume that this is the "preaching" mudra. Therefore, I have tentatively concluded that this Myogilsang is an image of the Shakyamuni offering the preaching mudra. There is no such combination of hand gestures in any other Goryeo-period images. The closest I could identify is the Beopjusa Rock-cut Buddha (fig. 7) from around the same time. 4. Comparative analysis: As seen in , except for the two contemporary paintings, all others on this chart are in ink or ink and light color. Also, none of them included the fact that the image is under a 40-meter cliff. In addition, the Joseon-period paintings all depicted the rock-cut image as if it were a human figure, using soft brushstrokes and rounded forms. None of these paintings accurately rendered the mudra from the image as did Seon-u. Only his painting depicts the natural setting of the image under the cliff along with a realistic rendering of the image. However, by painting the tall cliff in dark green and by eliminating elements on either side of the rock-cut image, the artist was able to create an almost surreal atmosphere surrounding the image. Herein lies the uniqueness of Seon-u Yeong's version. The left side of Seon-u's 2007 work Mount Geumgang (fig. 8) lives up to his reputation as a painter who depicts forms (rocks in this case) in minute detail, but in the right half of the composition it also shows his skill at presenting a sense of space. In contrast, Wave (fig. 9), a work completed one year before his death, displays his faithfulness to the traditions of ink painting. Even based on only three paintings by Seon-u Yeong, it seems possible to assess his versatility in both traditional ink and color mediums.