• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.4
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• pp.50-65
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• 2021

In this study, the water flow system by measuring the flow-way type and distance of flow path that composes the Gugok through literature survey, field survey, and map work on Gugok gardens in Korea whose existence has been confirmed, while investigating and analyzing watersheds, river orders, and river grades. It was intended to reveal the watershed distribution and stream morphological characteristics of the Gugok gardens and to use them as basic data for future enjoyment and conservation of the Gugok gardens. The conclusion of the study is as follows. First, Of the 93 Gugok gardens that have been confirmed to exist, it was found that 11 places(11.8%) were found to have a descending(top-down) type of Gugok that develops while descending along a stream. Second, As a result of analysis of the length of the flow path for each valley, Okryudonggugok(玉流洞九曲, Namsan-gugok) in Gimcheon, Gyeongsangbuk-do was found to have the shortest length of 0.44km among the surveyed valleys, while the flow distance of Muheulgugok(武屹九曲) located in Seongju-gun and Gimcheon-si, Gyeongsangbuk-do was 31.1km, showing the longest flowing distance. The average flow path length of the Gugok Garden in Korea was 6.24km, and the standard deviation was 4.63km, indicating that the deviation between the 'curved type'e and the 'valley type' was severe. In addition, 14(15.1%) Gugok gardens were found to be partially submerged due to dam construction. Third, As a result of analyzing the waters area where Gugok garden is located, the number of Nakdong river basins was much higher at 52 sites(55.9%), followed by the Hangang river basin at 27 sites(28.7%), the Geum river basin at 9 sites(9.7%), and the Yeongsan river and Seomjin river basins at 5(5.4%). Fourth, All Gugok gardens located in the Han river region were classified as the Han river system, and the Gugok garden located on the Nakdong river was classified as the main Nakdong river system, except for 7 places including 5 places in the Nakdong Gangnam Sea water system and 2 places in the Nakdong Gangdong sea water system. As a result of synthesizing the river order of the flow path where Gugok garden is located, Gugok, which uses the main stream as the base of Gugok, is 3 places in the Hangang water system, 5 places in the Nakdong river system, 2 places in the Geumgang water system, and 1 place in the Yeongsangam/Seomjin river system. A total of 11 locations(11.5%) were found, including 36 locations(38.2%) in the first branch, 29 locations(31.2%) in the second branch, and 16 locations(17.0%) in the third branch. And Gugok garden, located on the 4th tributary, was found to be Taehwa Five-gok(太華五曲) set in Yonghwacheon Stream in Cheorwon in the Han river system, and Hoenggyegok(橫溪九曲) in Yeongcheon Hoenggye Stream in the Nakdong river system. Fifth, As a result of the river grade analysis of the rivers located in the Gugok garden Forest, the grades of the rivers located in the Gugok garden were 13 national rivers(14.0%), 7 local first-class rivers(7.5%), and 74 local second-class rivers(78.5%) was shown.

• Korean Journal of Mineralogy and Petrology
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• v.34 no.1
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• pp.41-56
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• 2021

The characteristics of the six rock cleavages(R1~H2) in Jurassic Hapcheon granite were analyzed using the distribution of ① microcrack lengths(N=230), ② microcrack spacings(N=150) and ③ Brazilian tensile strengths(N=30). The 18 cumulative graphs for these three factors measured in the directions parallel to the six rock cleavages were mutually contrasted. The main results of the analysis are summarized as follows. First, the frequency ratio(%) of Brazilian tensile strength values(kg/㎠) divided into nine class intervals increases in the order of 60~70(3.3) < 140~150(6.7) < 100~110·110~120(10.0) < 90~100(13.3) < 80~90(16.7) < 120~130·130~140(20.0). The distribution curve of strength according to the frequency of each class interval shows a bimodal distribution. Second, the graphs for the length, spacing and tensile strength were arranged in the order of H2 < H1 < G2 < G1 < R2 < R1. Exponent difference(λS-λL, Δλ) between the two graphs for the spacing and length increases in the order of H2(-1.59) < H1(-0.02) < G2(0.25) < G1(0.63) < R2(1.59) < R1(1.96)(2 < 1). From the related chart, the six graphs for the tensile strength move gradually to the left direction with the increase of the above exponent difference. The negative slope(a) of the graphs for the tensile strength, suggesting a degree of uniformity of the texture, increases in the order of H((H1+H2)/2, 0.116) < G((G1+G2)/2, 0.125) < R((R1+R2)/2, 0.191). Third, the order of arrangement between the two graphs for the two directions that make up each rock cleavage(R1·R2(R), G1·G2(G), H1·H2(H)) were compared. The order of arrangement of the two graphs for the length and spacing is reverse order with each other. The two graphs for the spacing and tensile strength is mutually consistent in the order of arrangement. The exponent differences(ΔλL and ΔλS) for the length and spacing increase in the order of rift(R, -0.08) < grain(G, 0.14) < hardway(H, 0.75) and hardway(H, 0.16) < grain(G, 0.23) < rift(R, 0.45), respectively. Fourth, the general chart for the six graphs showing the distribution characteristics of the microcrack lengths, microcrack spacings and Brazilian tensile strengths were made. According to the range of length, the six graphs show orders of G2 < H2 < H1 < R2 < G1 < R1(< 7 mm) and G2 < H1 < H2 < R2 < G1 < R1(≦2.38 mm). The six graphs for the spacing intersect each other by forming a bottleneck near the point corresponding to the cumulative frequency of 12 and the spacing of 0.53 mm. Fifth, the six values of each parameter representing the six rock cleavages were arranged in the order of increasing and decreasing. Among the 8 parameters related to the length, the total length(Lt) and the graph(≦2.38 mm) are mutually congruent in order of arrangement. Among the 7 parameters related to the spacing, the frequency of spacing(N), the mean spacing(Sm) and the graph (≦5 mm) are mutually consistent in order of arrangement. In terms of order of arrangement, the values of the above three parameters for the spacing are consistent with the maximum tensile strengths belonging to group E. As shown in Table 8, the order of arrangement of these parameter values is useful for prior recognition of the six rock cleavages and the three quarrying planes.