• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.3
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• pp.195-214
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• 2020

The Samgwang Au-Ag deposit has been one of the largest deposits in Korea. The deposit consists of eight lens-shaped quartz veins which filled fractures along fault zones in Precambrian metasedimentary rock, which feature suggest that it is an orogenic-type deposit. The Ti-bearing minerals occur in wallrock (titanite, ilmenite and rutile) and laminated quartz vein (rutile). They occur minerals including biotite, muscovite, chlorite, white mica, monazite, zircon, apatite in wallrock and white mica, chlorite, arsenopyrite in laminated quartz vein. Chemical composition of titanite has maximum vaules of 3.94 wt.% (Al₂O₃), 0.49 wt.% (FeO), 0.52 wt.% (Nb₂O₅), 0.46 wt.% (Y₂O₃) and 0.43 wt.% (V₂O₅). Titanite with 0.06~0.14 (Fe/Al ratio) and 0.06~0.15 (X_Al (=Al/Al+Fe³⁺+Ti)) corresponds with metamorphic origin and low-Al variety. Chemical composition of ilmenite has maximum values of 0.07 wt.% (ZrO₂), 0.12 wt.% (HfO₂), 0.26 wt.% (Nb₂O₅), 0.04 wt.% (Sb₂O₅), 0.13 wt.% (Ta₂O₅), 2.62 wt.% (As₂O₅), 0.29 wt.% (V₂O₅), 0.12 wt.% (Al₂O₃) and 1.59 wt.% (ZnO). Chemical composition of rutile in wallrock and laminated quartz vein has maximum values of 0.35 wt.%, 0.65 wt.% (HfO₂), 2.52 wt.%, 0.19 wt.% (WO₃), 1.28 wt.%, 1.71 wt.% (Nb₂O₃), 0.03 wt.%, 0.07 wt.% (Sb₂O₃), 0.28 wt.%, 0.21 wt.% (As₂O₅), 0.68 wt.%, 0.70 wt.% (V₂O₃), 0.48 wt.%, 0.59 wt.% (Cr₂O₃), 0.70 wt.%, 1.90 wt.% (Al₂O₃) and 4.76 wt.%, 3.17 wt.% (FeO), respectively. Rutile in laminated quartz vein is higher contents (HfO₂, Nb₂O₃, As₂O₅, Cr₂O₃, Al₂O₃ and FeO) and lower content (WO₃) than rutile in wallrock. The substitutions of rutile in wallrock and laminated quatz vein are as followed : rutile in wallrock [(Fe³⁺, Al³⁺, Cr³⁺) + Hf⁴⁺ + (W⁵⁺, As⁵⁺, Nb⁵⁺) ⟵⟶ 2Ti⁴⁺ + V⁴⁺, 2Fe²⁺ + (Al³⁺, Cr³⁺) + Hf⁴⁺ + (W⁵⁺, As⁵⁺, Nb⁵⁺) ⟵⟶ 2Ti⁴⁺ + 2V⁴⁺], rutile in laminated quartz vein [(Fe³⁺, Al³⁺) + As⁵⁺ ⟵⟶ Ti⁴⁺ + V⁴⁺, (Fe³⁺, Al³⁺) + As⁵⁺ ⟵⟶ Ti⁴⁺ + Hf⁴⁺, 4(Fe³⁺, Al³⁺) ⟵⟶ Ti⁴⁺ + (W⁵⁺, Nb⁵⁺) + Cr³⁺], respectively. Based on these data, titanite, ilmenite and rutile in wallrock were formed by resolution and reconcentration of cations (W⁵⁺, Nb⁵⁺, As⁵⁺, Hf⁴⁺, V⁴⁺, Cr³⁺, Al³⁺, Fe³⁺, Fe²⁺) in minerals of wallrock during regional metamorphism. And then rutile in laminated quartz vein was formed by reconcentration of cations (Nb⁵⁺, As⁵⁺, Hf⁴⁺, Cr³⁺, Al³⁺, Fe³⁺, Fe²⁺) in alteration minerals (white mica, chlorite) and Ti-bearing minerals reaction between hydrothermal fluid originated during ductile shear and Ti-bearing minerals (titanite, ilmenite and rutile) in wallrock.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.69-98
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• 2009

We investigated what factors motivate gamers to participate in a guild and why they continue to be engaged as members of the guild. We find that, based on the result of focus group interviews with MMORPG gamers, social support and self-esteem factors play important roles. Considering both prior research and the focus group interviews we have conducted, we define social support and character control as independent variables. Character identity, guild identity, and self-esteem are proposed as mediating variables while guild flow and game loyalty as dependent variables. Accordingly, we develop the research model and hypotheses, and verify them empirically. Based on our experiences of playing the WoW game, we proposed a research model and conducted focus-group interviews (FGIs). FGIs involve formulating a hypothesis and then collecting some relevant data. FGIs were conducted face-to-face with students of C University in Korea. We formulated structured interview schedules, and the questions were based on our research variables and personal experiences. The questions for the interviews encompassed the following areas: (a) the demographic characteristics of the focus group; (b) the number of years for which respondents had played online games; (c) the motive for starting a game; (d) the number of game-characters assumed by each gamer; (e) the type of game played; and (f) other issues such as the reasons for involvement in the play, the willingness to reuse the game in case new versions were released, etc. On average, it took two hours to interview each of three groups. A primary set of FGIs was conducted with three groups on the premise that there would be some differences caused by character race (Horde vs. Alliance) or by playable server (Normal vs. Combat). With respect to the manner of playing, we found that guild members shared information, felt a sense of belonging, and played computer games for quite a long time through the guild; however, they did not undergo these experiences when playing alone. Gamers who belonged to a specific guild helped other players without expecting compensation for that, freely shared information about the game, gave away items for free, and more generous with other members who made mistakes. The guild members were aware of the existence other members and experienced a sense of belonging through interactions with, and evaluations from, other players. It was clear that social support was shown within the guild and that it played an important role as a major research variable. Based on the results of the first FGIs, a second set of in-depth FGIs was carried out with a focus on the psychology of the individual within the guild and the social community of the guild. The second set of FGIs also focused on the guild's offline meetings. Gamers, over all, recognize the necessity of joining a community, not only off-line but also online world of the guild. They admit that the guild is important for them to easily and conveniently enjoy playing online computer games. The active behavior and positive attitudes of existing guild members can motivate new members of the guild to adapt themselves to the guild environment. They then adopt the same behaviors and attitudes of established guild members. In this manner, the new members of the guild strengthen the bonds with other gamers while feeling a sense of belonging, and developing social identity, thereby. It was discovered that the interaction among guild members and the social support encouraged new gamers to quickly develop a sense of social identity and increase their self-esteem. The guild seemed to play the role of socializing gamers. Sometimes, even in the real world, the guild members helped one another; therefore, the features of the guild also spilled over to the offline environment. We intend to use self-esteem, which was found through the second set of FGIs, as an important research variable. To collect data, an online survey was designed with a questionnaire to be completed by WoW gamers, who belong to a guild. The survey was registered on the best three domestic game-sites: 'WoW playforum,' 'WoW gamemeca,' and 'Wow invent.' The selected items to be measured in the questionnaire were decided based on prior research and data from FGIs. To verify the content of the questionnaire, we carried out a pilot test with the same participants to point out ambiguous questions as a way to ensure maximum accuracy of the survey result. A total of 244 responses were analyzed from the 250 completed questionnaires. The SEM analysis was used to test goodness-of-fit of the model. As a result, we found important results as follows: First, according to the statistics, social support had statistically significant impacts on character control, character identity, guild identity and self-esteem. Second, character control had significant effects on character identity, guild identity and self-esteem. Third, character identity shows its clear impact on self-esteem and game loyalty. Fourth, guild identity affected self-esteem, guild flow and game loyalty. Fifth, self-esteem had a positive influence on the guild flow. These days, the number of virtual community is rising along with its significance largely because of the nature of the online games. Accordingly, this study is designed to clarify the psychological relationship between gamers within the guild that has been generally established by gamers to play online games together. This study focuses on the relationships in which social support influences guild flow or game loyalty through character control, character identity, guild identity, and self-esteem, which are present within a guild in the MMORPG game environment. The study results are as follows. First, the effects of social support on character control, character identity, guild identity and self-esteem are proven to be statistically significant. It was found that character control improves character identity, guild identity and self-esteem. Among the seven variables, social support, which is derived from FGIs, plays an important role in this study. With the active support of other guild members, gamers can improve their ability to develop good characters and to control them. Second, character identity has a positive effect on self-esteem and game loyalty, while guild identity has a significant effect on self-esteem, guild flow and game loyalty. Self-esteem affects guild flow. It was found that the higher the character and guild identities become, the greater the self-esteem is established. Contrary to the findings of prior research, our study results indicate that the relationship between character identity and guild flow is not significant. Rather, it was found that character identity directly affects game players' loyalty. Even though the character identity had no direct effect on increasing guild flow, it has indirectly affected guild flow through self-esteem. The significant relationship between self-esteem and guild flow indicates that gamers achieve flow, i.e., a feeling of pleasure and excitement through social support. Several important implications of this study should be noted. First, both qualitative and quantitative methods were used to conduct this study. Through FGIs, it was observed that both social support and self-esteem are important variables. Second, because guilds had been rarely studied, this research is expected to play an important role in the online community. Third, according to the result, six hypotheses (H1, H5, H6, H7, H8, and H11) setup based on FGIs, were statistically significant; thus, we can suggest the corresponding relationships among the variables as a guideline for follow-up research. Our research is significant as it has following implications: first, the social support of the guild members is important when establishing character control, character identity, guildidentity and self-esteem. It is also a major variable that affects guild flow and game loyalty. Second, character control when improved by social support shows notable influence on the development of character identity, guild identity and self-esteem. Third, character identity and guild identity are major factors to help establish gamers' own self-esteem. Fourth, character identity affects guild flow through self-esteem and game loyalty. The gamers usually express themselves through characters; the higher character identity is, the more loyalty a gamer has. Fifth, guild identity, established within the guild, has clear effects on self-esteem, guild flow and game loyalty. Sixth, qualitative and quantitative methods are employed to conduct this study. Based on the results of focus group interviews and SEM analysis, we find that the social support by guild members and psychological factors are significant in strengthening the flow of guild and loyalty to the game. As such, game developers should provide some extra functions for guild community, through which gamers can play online games in collaboration with one another. Also, we suggest that positive self-esteem which is built up through social support can help gamers achieve higher level of flow and satisfaction, which will consequently contribute to minimizing the possibility for the players to develop negative attitude toward the guild they belong to.

• Journal of Korean Society of Forest Science
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• v.62 no.1
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• pp.24-42
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• 1983

To develop Ilex cornuta which grow naturally in the southwest seaside district as new ornamental tree, the author chose I. cornuta growing in the four natural communities and those cultivated in Kwangju city as a sample, and investigated its ecology, morphology and characteristics. The results obtained was summarized as follows; 1) The natural distribution of I. cornuta marks $35^{\circ}$43'N and $126^{\circ}$44'E in the southwestern part of Korea and $33^{\circ}$20'N and $126^{\circ}$15'E in Jejoo island. This area has the following necessary conditions for Ilex cornuta: the annual average temperature is above $12^{\circ}C$, the coldness index below $-12.7^{\circ}C$, annual average relative humidity 75-80%, and the number of snow-covering days is 20-25 days, situated within 20km of from coastline and within, 100m above sea level and mainly at the foot of the mountain facing the southeast. 2) The vegetation in I. cornuta community can be divided that upper layer is composed of Pinus thunbergii and P. densiflora, middle layer of Eurya japonica var. montana, Ilex cornuta and Vaccinium bracteatum, and the ground vegetation is composed of Carex lanceolata and Arundinella hirta var. ciliare. The community has high species diversity which indicates it is at the stage of development. Although I. cornuta is a species of the southern type of temperate zone where coniferous tree or broad leaved, evergreen trees grow together, it occasionally grows in the subtropical zone. 3) Parent rock is gneiss or rhyolite etc., and soil is acidic (about pH 4.5-5.0) and the content of available phosphorus is low. 4) At maturity, the height growth averaged $10.48{\pm}0.23cm$ a year and the diameter growth 0.43 cm a year, and the annual ring was not clear. Mean leaf-number was 11.34. There are a significant positive correlation between twig-elongation and leaf-number. 5) One-year-old seedling grows up to 10.66 cm (max. 18.2 cm, min. 4.0 cm) in shoot-height, with its leaf number 12.1 (max. 18, min), its basal diameter 2.24 mm (max. 4.0 mm, min. 1.0 mm) and shows rhythmical growth in high temperature period. There were significant positive correlations between stalk-height and leaf-number, between stalk-height and basal-diameter, and between number and basal diameter. 6) The flowering time ranged from the end of April to the beginning of May, and the flower has tetra-merouscorella and corymb of yellowish green. It has a bisexual flower and dioecism with a sexual ratio 1:1. 7) The fruit, after fertilization, grows 0.87 cm long (0.61-1.31 cm) and 0.8 cm wide (0.62-1.05 cm) by the beginning of May. Fruits begin to turn red and continue to ripen until the end of October or the beginning of November and remain unfading until the end of following May. With the partial change in color of dark-brown at the beginning of the June fruits begin to fall, bur some remain even after three years. 8) The seed acquision ratio is 24.7% by weight, and the number of grains per fruit averages 3.9 and the seed weight per liter is 114.2 gram, while the average weight of 1,000 seeds is 24.56 grams. 9) Seeds after complete removal of sarcocarp, were buried under ground in a fixed temperature and humidity and they began to develop root in October, a year later and germinated in the next April. Under sunlight or drought, however, the dormant state may be continued.