• Journal of information and communication convergence engineering
• /
• 제10권1호
• /
• pp.27-32
• /
• 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.

• 복식문화연구
• /
• 제25권1호
• /
• pp.32-47
• /
• 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.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
• /
• pp.333-340
• /
• 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.

• 지능정보연구
• /
• 제6권2호
• /
• pp.63-76
• /
• 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.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권12호
• /
• pp.1660-1671
• /
• 2004

본 논문은 두 문서간 유사도 측정 방법을 제안한다. 제안한 유사도 측정 모델의 주안점은 문서간 관련성의 정도를 두 문서간 일치하는 단어(term)및 단어쌍(tenn-phrase)에 기반하여 이들이 해당 문서에서 차지하는 가중치를 통해 측정하는 것이다. 유사도 측정 과정에 영향을 미치는 특징을 설계함에 있어 기존의 연구들이 하나의 특징만을 고려하였던 것에 비하여 본 논문은 여러 가지 특징들을 고려한다 즉, 단어뿐만 아니라 단어쌍과 관련된 특징을 결합하여 신경망을 통해 유사도를 측정한다. 제안된 방법의 우수성을 입증하기 위해 두 가지 측면에서 실험하였다. 첫 번째는 두 문서의 동일성 여부를 검증하는 문제이며, 두 번째는 다수의 문서를 대상으로 유사한 문서를 찾는 검색 문제이다. 이 두 가지 실험 모두에서 제안 방법이 기존의 Cosine 유사도 계산 방법 및 구색인 방법에 비해 우수한 성능을 보였다.

• International Journal of Computer Science & Network Security
• /
• 제21권1호
• /
• pp.97-106
• /
• 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.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제46권3호
• /
• pp.315-329
• /
• 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
• /
• 제22권5호
• /
• pp.163-167
• /
• 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.

• 한국콘텐츠학회논문지
• /
• 제16권4호
• /
• pp.275-288
• /
• 2016

제시되는 시각 자극의 모호함에 따라 디자인 아이디어의 창의성이 어떻게 달라지는지 알아보기 위해 시각자극의 모호함의 세 가지 수준 (Vague, Ambiguous, Definite) 과 아이디어 교류 유무(Idea sharing Before & After)의 두 가지 수준으로 아이디어 스케치들을 구분하여 의사결정나무분석법을 시행하였다. 그리고 이를 통해 각 그룹의 아이디어 스케치의 창의성 예측점수와 그 예측점수에 영향을 끼친 변인은 무엇인지 그리고 그 기준은 어떠한지 살펴보았다. 분석 결과, 시각 자극의 모호함과 아이디어 교류의 유무에 따라 아이디어 스케치의 창의성 예측 점수가 높은 경우에 있어 중요한 영향을 미친 예측변수들은 종결저항, 독창성, 정교성, 추상성, 컨셉쌍 간의 유사도로 나타났다. 즉, 이 5가지 변수들은 유창성과 개념결합전략, 새 개념의 등장여부, 개인 창의력 지수, 창의적 문제해결성향보다 디자인 아이디어 스케치의 창의성에 더 연관이 있는 요인들임을 알 수 있었다. 그리고 아이디어 교류 후, Vague 자극을 제시 받은 집단이 창의성 예측값이 가장 높게 나타났고, 아이디어 교류 후, Definite 자극을 제시 받은 집단이 창의성 예측값이 가장 낮게 나타났다.

• International Journal of Knowledge Content Development & Technology
• /
• 제9권3호
• /
• pp.23-41
• /
• 2019

This study combines the concept of degree centrality in complex network with the Term Frequency $^*$ Proportional Document Frequency ($TF^*PDF$) algorithm; the combined method, called PMCN (PDF-Modified similarity and Complex Network), constructs relationship networks among sentences for writing news summaries. The PMCN method is a multi-document summarization extension of the ideas of Bun and Ishizuka (2002), who first published the $TF^*PDF$ algorithm for detecting hot topics. In their $TF^*PDF$ algorithm, Bun and Ishizuka defined the publisher of a news item as its channel. If the PDF weight of a term is higher than the weights of other terms, then the term is hotter than the other terms. However, this study attempts to develop summaries for news items. Because the $TF^*PDF$ algorithm summarizes daily news, PMCN replaces the concept of "channel" with "the date of the news event", and uses the resulting chronicle ordering for a multi-document summarization algorithm, of which the F-measure scores were 0.042 and 0.051 higher than LexRank for the famous d30001t and d30003t tasks, respectively.