• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.467-485
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• 2024

Policymakers and educational researchers have grown increasingly interested in the extent to which study results generalize across different groups of students. Current generalization research in education has largely focused on the compositional similarity among students based on a set of observable characteristics. However, generalization is defined differently across various disciplines. While the concept of compositional similarity is prominent in causal research, generalization among the statistical learning community refers to the extent to which a model produces accurate predictions across samples and populations. The purpose of this study is to assess the extent to which concepts related to contextual generalization (based on compositional similarity) are associated with the ideas related to model generalization (based on accuracy of prediction). We use observational data from the Programme for International Student Assessment (PISA) 2015 wave as a case study to examine the conditions under which contextual and model generalization are aligned. We assess the correlations between statistical measures that quantify compositional similarity and prediction accuracy and discuss the implications for generalization research.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.27-32
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• 2012

Twitter can spread and share all kinds of information such as facts, opinions, and ideas in real time. In this paper, we empirically compare and analyze the topic categories in Twitter with all top 100 users in each of geographic region. We mainly consider the relationships among regions and selected four regions: Global, Seoul, Tokyo, and Beijing. Each of the top 100 users in Twitter is classified into a specific category and then statistical analysis is conducted. Among eight topic categories, the "Arts" category is the largest and the second is "Life". The correlation between global and Seoul groups has the lowest value among the six pairs of relationships between regional groups, and this difference is statistically significant. We find that the Seoul, Tokyo, and Beijing regional Twitter groups, all in East Asia, have high topical similarity. Based on the correlation analysis, Seoul and Tokyo saliently show a sticky trend. The correlation coefficient presents very a strong positive correlation between Seoul and Tokyo. The correlation between the global group and the East Asian groups is relatively lower than that among the East Asian groups.

• The Research Journal of the Costume Culture
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• v.25 no.1
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• pp.32-47
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• 2017

As the popularity of Korean drama and celebrities in China, Korean fashion is becoming increasingly popular in the Chinese market. Although the effect of Korean drama on Chinse consumers' attitudes toward Korean products are known, little research has been conducted to understand the mechanisms underlying the impact of Korean drama on the development of consumer attitudes. Thus, this study examines how Chinese consumers' exposure to Korean dramas has influenced their attitudes towards Korean fashion products. Applying the similarity-attraction theory, the study explores the roles Chinese consumers' perceived similarities in appearance and values with Korean characters in TV dramas plays in the process of attitude development. Data was collected via an online survey and the responses of 317 Chinese consumers in their twenties were used for data analysis. The results of structural equation modeling show that exposure to Korean dramas has a direct impact on Chinese consumers' perceived appearance similarity, perceived value similarity, image of Korean people, and attitudes toward Korean fashion products-results that support the theory of mere exposure. In addition, the analysis demonstrates that perceived appearance similarity positively influences the image of Koreans among Chinese people, which, in turn, influences attitudes toward Korean fashion products, supporting the similarity-attraction theory. However, the effect of perceived value similarity on attitude toward Korean fashion products was not significant. The study concludes by describing its practical implications for the Korean fashion industry and presenting ideas for future research.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.333-340
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• 2000

Research on group decisions and electronic meeting systems have been increasing rapidly according to the widespread of Internet technology. Although various issues have been raised in empirical research, we will try to solve an issue on idea categorizing in the group decision making process of electronic meeting systems. Idea categorizing used at existing group decision support systems was performed in a top-down procedure and mostly b participants; manual work. This resulted in tacking as long in idea categorizing as it does for idea generating clustering an idea in multiple categories, and identifying almost similar redundant categories. However such methods have critical limitation in the electronic meeting systems, we suggest an intelligent idea categorizing methodology which is a bottom-up approach. This method consists of steps to present idea using keywords, identifying keywords' affinity, computing similarity among ideas, and clustering ideas. This methodology allows participants to interact iteratively for clear manifestation of ambiguous ideas. We also developed a prototype system, IIC (intelligent idea categorizer) and evaluated its performance using the comparision experimetn with other systems. IIC is not a general purposed system, but it produces a good result in a given specific domain.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.63-76
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• 2000

Research on group decisions and electroinc meeting systems have been increasing rapidly according to the widespread of Internet technology. Although various issues have been raised in empirical research, we will try to solve an issue on idea categorizing in the group decision making process of elecronic meeting systems. Idea categorizing used at existing group decision support systems was performed in a top-down procedure and mostly participants\` by manual work. This resulted in tacking as long in idea categorizing as it does for idea generating, clustering an idea in multiple categories, and identifying almost similar redundant categories. However such methods have critical limitation in the electronic meeting systems, we suggest an intelligent idea categorizing methodology which is a bottom-up approach. This method consists of steps to present idea using keywords, identifying keywords\` affinity, computing similarity among ideas, and clustering ideas. This methodology allows participants to interact iteratively for clear manifestation of ambiguous ideas. We also developed a prototype system, IIC (intelligent idea categorizer) and evaluated its performance using the comparision experimetn with other systems. IIC is not a general purposed system, but it produces a good result in a given specific domain.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1660-1671
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• 2004

This paper proposes a method for measuring document similarity between two documents. One of the most significant ideas of the method is to estimate the degree of similarity between two documents based on the frequencies of terms and term-pair, existing in both the two documents. In contrast to conventional methods which takes only one feature into account, the proposed method considers several features at the same time and meatures the similarity using a neural network. To prove the superiority of our method, two experiments have been conducted. One is to verify whether the two input documents are from the same document or not. The other is a problem of information retrieval with a document as the query against a large number of documents. In both the two experiments, the proposed method shows higher accuracy than two conventional methods, Cosine similarity measurement and a term-pair method.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.97-106
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• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• The Mathematical Education
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• v.46 no.3
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• pp.315-329
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• 2007

The concepts of ratio, rate, and proportion are used in everyday life and are also applied to many disciplines such as mathematics and science. Proportional reasoning is known as one of the pivotal ideas in school mathematics because it links elementary ideas to deeper concepts of mathematics and science. However, previous research has shown that it is difficult for students to recognize the proportionality in contextualized situations. The purpose of this study is to understand how the mathematical concept in the middle school mathematics curriculum is connected with ratio, rate, and proportion and to investigate the characteristics of proportional reasoning through analyzing the concept including ratio, rate, and proportion on the middle school mathematics curriculum. This study also examines mathematical concepts (direct proportion, slope, and similarity) presented in a middle school textbook by exploring diverse interpretations among ratio, rate, and proportion and by comparing findings from literature on proportional reasoning. Our textbook analysis indicated that mechanical formal were emphasized in problems connected with ratio, rate, and proportion. Also, there were limited contextualizations of problems and tasks in the textbook so that it might not be enough to develop students' proportional reasoning.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.163-167
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• 2022

The article explores linguo-stylistic influence markers in essayistic texts. The novelty of this investigation is provided by its perspective. Essayism is looked at as a style of thinking and writing and studied as a holistic philosophical and cultural phenomenon, as a revalent form of comprehension of reality that features non-lasting author's judgements and enhancement of the author's voice in the text. Based on the texts by V. Rosanov, G.K. Chesterton, and D. Dontsov, the remarkable English, Russian, and Ukrainian essay-writers of the first party of the 20th century, the article tracks the typical ontological-and-existentialist correlation at the content, stylistic, and semantic levels. It is observed in terms of the ideas presented in the texts of these publicists and the lexicostylistic markers of the influence on the reader that enable these ideas to implement. The explored poetic syntax, key lexemes, dialogueness, intonational melodics, specific language, free associations, aphoristic nature, verbalization of emotions and feeling in the psycholinguistic form of their expression, stress, heroic elevation, metaphors and evaluative linguistic units in the ontological-and-existentialist aspects contribute to extremely delicate and demanding nature of the essayistic style. They create a "lacework" of unpredictable properties, intellectual illumination, unexpected similarity, metaphorical freshness, sudden discoveries, unmotivated unities.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.275-288
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• 2016

A decision tree analysis was performed by categorizing the idea sketches produced in the group environment into three different levels of visual stimuli ambiguity (vague, ambiguous, and definite) and two idea-sharing situations (before and after). We then examined the predicted values for the creativity of each group's idea sketches, the factors that led to high creativity scores, and their standards. The results of the analyses indicated that the Resistance to Premature Closure, Originality, Elaboration, ness, and Similarity represented important predictors of the creativity of design idea sketches according to the level of ambiguity of the visual stimuli used and whether ideas were shared or not. The group presented with vague stimuli after sharing ideas scored the highest predicted creativity value and the group presented with definite stimuli after sharing ideas scored the lowest predicted creativity value.