• 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.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.317-326
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• 2021

The purpose of this study is to identify Actor and Partner Effects of Marital Intimacy according to Personality Characteristics of Couples Participating in Dance Sports. The study participants collected data on 148 couples participating in dance sports. After analyzing the APIM model using SPSS 25.0 and AMOS 25.0 to solve the research problem, The following conclusions were obtained the following conclusions were obtained: First, there were significant differences between husband and wife in relation to neurosis among personality traits, and the wife's neurosis about the husband's marital intimacy was affected by amulets and the wife was found to have relatively low static effects. Second, there were significant differences only to the husband in relation to openness among personality characteristics, and the wife's openness to the husband's marital intimacy was found to be relatively malleable, and the wife was found to be subject to the same level of static influence. Third, there were significant differences in personality traits in relation to extroversion only to the wife, and it was found that the wife was subject to relatively low static influence. Fourth, there were no significant differences between husband and wife in relation to sincerity among personality characteristics and they appeared to have a static effect on each other. Fifth, significant differences were found only to the wife in relation to affinity among personality characteristics, and the wife was found to be subject to relatively low static influence.

• Communications of Mathematical Education
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• v.20 no.2 s.26
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• pp.295-326
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• 2006

Despite the importance of mathematics education, many students in high school have lost their interests and felt difficulties and they don't have 'mathematical' experience with meanings attached because of the entrance examination. This paper attempted to resolve these problems and find the teaching-method with which students can study by themselves with more confidence. Nowadays students' use of Internet is very popular. After develop 'the development of mathematical power' program based on mathematics history, history, science, the application of problems in real world, and self-evaluation, I made students repeat them after making teaching lessons in classroom as moving pictures. Through this processes, I attempted to develop the Self-Directed Learning' ability by making public education substantial. First of all I analyzed the actual conditions on 'Self-Directed Learning' ability in mathematics subject, the conditions of seeing and hearing in Internet learning program, and students' and their parents' interests in Internet education. By analyzing the records, I observed the significance of the introducing mathematics history in mathematics subject in early stager, cooperative-learning, leveled-learning, self-directed learning, and Internet learning. Actually in aspect of applying 'the development of mathematical power' program, at first I made up the educational conditions to fix the program, collected the teaching materials, established the system of teaching-learning model, developed materials for the learning applying Internet mail and instruments of classroom, and carried out instruction to establish and practice mathematics learning plan. Then I applied the teaching-learning model of leveled cooperation and presentation loaming and at the same time constructed and used the leveled learning materials of complementary, average, and advanced process and instructed to watch teaching moving pictures through Internet mail and in the classroom. After that I observed how effective this program was through the interest arid attitude toward mathematics subject, learning accomplishment, and the change of self-directed learning. Finally, I wrote the conclusion and suggestion on the preparation of conditions fur the students' voluntary participation in mathematics learning and the project and application on 'the development of mathematical power' program and repeated learning with the materials of moving pictures in classroom.