• 한국의상디자인학회지
• /
• 제14권2호
• /
• pp.147-156
• /
• 2012

The purpose of this study is to analyze the style of wide pants shown in collections from 2008 to 2011 and to extract main expressional words for the development of semantic differential scales of visual images according to the change in silhouette of wide pants. The results of this study are as follows: 1) The wide pants which women wore in the 1970s were similar to men's. The aesthetic values for the wide pants included the social women's requests of the time. On the other hand, new wide pants shown in the current collections have diversified by adding designers' will to express contemporary women's tastes and fashion senses. 2) 742 wide pants shown in collections were composed of 459 straight, 147 bell-bottom and 136 flared pants. The design differs according to changes in the waist position and width of the wide pants. 3) Main expressional words of visual images for wide pants differ greatly depending on the silhouette of wide pants. The visual images are ranked in the order of 'showed that legs are long', 'looked taller', 'neat', 'relaxed', 'retro', 'modern' for straight pants. The words of 'retro', 'countrified', 'legs seemed to be long', 'enough' 'confident' 'looked like thighs that are slim' are ranked for bell-bottom pants. And the words of 'plentiful' 'loose', 'enough', 'retro' 'uncomfortable', 'relaxed', 'countrified' are marked down for flared pants.

• 한국컴퓨터정보학회논문지
• /
• 제22권12호
• /
• pp.117-123
• /
• 2017

The personalized search algorithm is a search system that analyzes the user's IP, cookies, log data, and search history to recommend the desired information. As a result, users are isolated in the information frame recommended by the algorithm. This is called 'Filter bubble' phenomenon. Most of the personalized data can be deleted or changed by the user, but data stored in the service provider's server is difficult to access. This study suggests a way to neutralize personalization by keeping on sending random query words. This is to confuse the data accumulated in the server while performing search activities with words that are not related to the user. We have analyzed the rank change of the URL while conducting the search activity with 500 random query words once using the personalized account as the experimental group. To prove the effect, we set up a new account and set it as a control. We then searched the same set of queries with these two accounts, stored the URL data, and scored the rank variation. The URLs ranked on the upper page are weighted more than the lower-ranked URLs. At the beginning of the experiment, the difference between the scores of the two accounts was insignificant. As experiments continue, the number of random query words accumulated in the server increases and results show meaningful difference.

• 컴퓨터교육학회논문지
• /
• 제5권1호
• /
• pp.109-115
• /
• 2002

인터넷이 교육에 사용됨으로써 학습자의 자기주도학습, 개별학습, 완전학습, 그리고 탐구형 학습 등이 효과적으로 이루어질 수 있다. 특히 이러한 장점을 취하기 위하여 게시판 시스템이 웹 기반 학습에 널리 사용되고 있다. 그러나, 게시판의 활용은 인터넷이 가지는 익명성으로 인해 자유로운 의견의 교환이라는 장점 외에, 부정적이거나 폭력적인 언어 사용이 쉽게 일어난다는 단점을 가진다. 본 연구는 인터넷을 활용한 학습에서 커뮤니케이션 도구로 널리 사용되고 있는 게시판이 유해단어 관리 기능을 가지도록 함으로써, 유해한 내용을 포함하는 내용의 게시를 제재하고 학생들의 언어 습관을 교정 할 수 있게 하였다.

• 한국의류학회지
• /
• 제43권2호
• /
• pp.255-273
• /
• 2019

Perceptions of beauty change and are shared with others in the media of emotional words. In the modern age, a mix of traditional and modern make-up cultures has changed the standards of beauty. Therefore, an analysis using emotional words (an image that consumers have for certain subjects) and an image scale that intuitively shows them can be an important means for understanding changes in the "beauty of the time". This paper considered changes in typical aesthetic characteristics that women pursued through make-up by analyzing emotional words in white make-up powder advertisement texts from the 1920s through the 1930s. Imported modern technologies changed cosmetic manufacturing techniques and advertising methods to create a momentum that changed women's make-up culture from light to heavy make-up or from white to color make-up. Such changes have led to changes in the perception of beauty and were expressed through sensitive vocabularies such as pure, new, fresh, lofty, lively, healthy, and cheery. Such changes reflect social aspects such as women's aspirations for high status, pursuit of security, or women's roles under the wartime regime to show a change from beauty with an attribute of [+cool] to that of [+soft].

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권11호
• /
• pp.4184-4202
• /
• 2021

Text steganography combined with natural language generation has become increasingly popular. The existing methods usually embed secret information in the generated word by controlling the sampling in the process of text generation. A candidate pool will be constructed by greedy strategy, and only the words with high probability will be encoded, which damages the statistical law of the texts and seriously affects the security of steganography. In order to reduce the influence of the candidate pool on the statistical imperceptibility of steganography, we propose a steganography method based on a new sampling strategy. Instead of just consisting of words with high probability, we select words with relatively small difference from the actual sample of the language model to build a candidate pool, thus keeping consistency with the probability distribution of the language model. What's more, we encode the candidate words according to their probability similarity with the target word, which can further maintain the probability distribution. Experimental results show that the proposed method can outperform the state-of-the-art steganographic methods in terms of security performance.

• 한국의류산업학회지
• /
• 제25권1호
• /
• pp.72-81
• /
• 2023

As changes in social and economic paradigms are accelerating, and non-contact has become the new normal due to the COVID-19 pandemic, metaverse services that build societies in online activities and virtual reality are spreading rapidly. This study analyzes the perception and trend of metaverse fashion using big data. TEXTOM was used to extract metaverse and fashion-related words from Naver and Google and analyze their frequency and importance. Additionally, structural equivalence analysis based on the derived main words was conducted to identify the perception and trend of metaverse fashion. The following results were obtained: First, term frequency(TF) analysis revealed the most frequently appearing words were "metaverse," "fashion," "virtual," "brand," "platform," "digital," "world," "Zepeto," "company," and "game." After analyzing TF-inverse document frequency(TF-IDF), "virtual" was the most important, followed by "brand," "platform," "Zepeto," "digital," "world," "industry," "game," "fashion show," and "industry." "Metaverse" and "fashion" were found to have a high TF but low TF-IDF. Further, words such as "virtual," "brand," "platform," "Zepeto," and "digital" had a higher TF-IDF ranking than TF, indicating that they had high importance in the text. Second, convergence of iterated correlations analysis using UNICET revealed four clusters, classified as "virtual world," "metaverse distribution platform," "fashion contents technology investment," and "metaverse fashion week." Fashion brands are hosting virtual fashion shows and stores on metaverse platforms where the virtual and real worlds coexist, and investment in developing metaverse-related technologies is under way.

• Journal of Preventive Medicine and Public Health
• /
• 제32권1호
• /
• pp.72-79
• /
• 1999

Objectives. The purpose of this study was to evaluate the quality of abstracts of original articles. Methods. This subjects selected total 63 abstracts of the original articles of the Korean Journal of Preventive Medicine in 1997. The quality of abstracts was measured against a checklist of evaluation criteria, which were divided into eight categories and the numbers of inappropriate words (including grammar) according to criterionbased survey. A score for each abstract was obtained by dividing the number of criteria presented by the number applicable. The overall mean score was also determined. Results. The overall mean score of abstract quality was 0.55 out of 1. Of the abstracts subject selection 83% didn't include specific technical descriptors. Of those that gave conclusions 92% didn't address study limitations and 78% made no recommendations for future study. The overall mean number of inappropriate usage of words (including grammar) per abstract was 14.1. The overall mean number of English words was 283. In the multiple regression analyses, the research career of the first author and the number of English words to the number of inappropriate usage of words were statistically significant. Also, in the secondary regression model, the number of English words to the quality score of abstract was only statistically significant. Conclusions. Most of the abstracts provided some information pertaining to each evaluation criterion. However, they did not provide sufficient details to enhance the reader's understanding of the article. On the basis of the study the abstracts need improvement in its description of the reported subject selection, statements of limitations and recommendations, etc. The Korean Society for Preventive Medicine will recommend a proposal for more informative abstracts in Korean J Prey Med and will take into consideration the introduction of foreign review of abstracts. Future studies should address these issues and compare the quality of abstracts between different journals and their time of publication.

• 인터넷정보학회논문지
• /
• 제11권6호
• /
• pp.41-50
• /
• 2010

인간은 어떤 정보를 기억하려 노력하더라도, 시간이 지남에 따라 그 정보의 대부분을 잊어버린다. 반면에 인간은 사진을 보며 대부분 잊혀진 과거의 기억을 떠올릴 뿐만 아니라, 사진 속에 존재하는 특정 물체로부터 여러 단어들을 연상한 뒤, 그 연상된 단어로부터 새로운 기억을 떠올리곤 한다. 또한 이렇게 떠올린 기억으로 그 당시의 감성을 느끼기도 한다. 따라서 본 논문은 소셜 네트워크 서비스에 업로드된 사진들과 개인의 연상 단어 사전을 활용하여 사용자의 과거 회상에 도움이 되는 증강 기억 시스템을 제안한다. 제안하는 시스템에서 사용자가 특정 사진 속에 존재하는 물체를 선택하면, 그 물체와 관련된 연상 단어가 사용자에게 제공된다. 만일 사용자가 연상 단어중 하나를 선택하면, 제안하는 시스템은 해당 단어의 물체를 포함하는 다른 사진들의 목록을 사용자에게 제공함으로써, 사용자의 기억 회상을 돕고 감성을 자극할 수 있다. 본 논문에서 제안하는 시스템은 소셜 네트워크 서비스에서 보다 다양한 콘텐츠를 제공할 수 있을 것으로 기대 된다.

• 인지과학
• /
• 제15권2호
• /
• pp.33-42
• /
• 2004

일본어와 한국어는 문법적으로 많은 유사점을 가지고 있다. 이러한 유사점을 잘 이용한다면 일한 기계번역 시스템에서 구문해석이나 의미해석의 상당한 부분을 생략할 수 있다. 몇 년 전부터 우리는 유사성을 이용하여 번역율을 높이는 방법으로 번역테이블을 이용한 일한기계번역 시스템을 연구해왔다. 그러나 이 시스템은 활용어미의 번역, 다의성 단어의 처리 등 및 가지 문제점을 가지고 있었다. 본 논문에서는 번역데이블을 이용하는 시스템을 개선하여 이웃하는 단어들과의 관계 정보를 이용한 일한 기계번역 시스템을 제안한다. 현재 시스템의 문제점들을 해결하기 위하여 우선 조사, 조동사의 접속정보를 최대한 이용한다. 또한, 번역 테이블을 엔트리테이블과 접속정보 테이블로 나누어 설계하여 번역의 효율을 높인다. 즉, 하나의 역어만 가지는 단어인 경우, 우리는 일한 직접 대응 방법을 이용하여 바로 번역하고 2개 이상의 역어로 번역되어야 할 경우만 접속 정보 값을 평가하여 가장 가능성이 높은 번역어를 선택하도록 한다.

• 정보처리학회논문지B
• /
• 제13B권1호
• /
• pp.71-76
• /
• 2006

기계번역에서 올바른 번역 문장을 구성하기 위해서는 원시 문장의 의미를 올바르게 표현하면서 자연스러운 목적 문장을 구성하는 번역어를 선택해야 한다. 본 논문에서는 '단어-의미 의미-단어' 관계, 즉 원시언어의 한 단어는 하나 이상의 의미를 가지고 각 의미는 각기 다른 목적언어 단어로 표현된다는 점에 기반하여, 원시 단어의 의미 분별과 목적 단어 선택을 결합하여 번역어를 선택하는 방식을 제안한다. 기존의 번역방식은 원시 단어에 대한 목적단어를 직접 선택하는 '단어-단어' 관계에 기반하고 있기 때문에, 원시언어를 목적 언어로 직접 대응시키기 위한 지식을 필요로 하여 지식 획득에 어려움이 있었다. 본 논문의 방식에서는 원시 단어의 의미 분별과 목적 언어의 단어 선택의 결합을 통해 번역어를 선택함으로써, 손쉽게 획득할 수 있는 원시 언어와 목적 언어 각각의 지식원에서 번역어 선택을 위한 지식을 자동으로 추출할 수 있다. 또한 원시 언어의 의미와 목적 언어의 쓰임새를 모두 반영하여 충실도와 이해도를 모두 만족시키는 보다 정확한 번역어를 선택할 수 있다.