• Science of Emotion and Sensibility
• /
• v.14 no.4
• /
• pp.593-604
• /
• 2011

This study examines potential growth and different perspectives on green-walls, which are being re-evaluated recently. The aim is to identify the viewer preferences concerning the walls by collecting a wide spectrum of information to create an interior design related comprehensive and intellectual database. Also based on this proposition, choosing a green surface of indoor wall as a specific example stimulus, identifying a relationship betweeationsviewer's preference factors. The relationship will formulate detailed and absolute qualities, which will reach potential areas that the green walls can be widely applied in. As a result of a factor analysis, the viewers classified into the 3 factors as is pleasant, gorgeous and rich about the stimulus. Preferred key factors, which are closely related to emotional image language, were; cool, tidy, comfortable and beautiful. The common factors in preferred design stimulus, in order of importance are color>elements>image/form/plants. Specific levels of design factors according to relevance are contrast>furniture> modern>central/creeper foliage plants. In the meantime, this study is leading the process of quantitative measurement of green-walls to a new design direction and it is critical to consistently experimenting to back up the theory with solid evidence.

• Journal of KIISE:Software and Applications
• /
• v.37 no.1
• /
• pp.60-73
• /
• 2010

This paper aims to describe KorLexClas 1.5 which provides us with a very large list of Korean numeral classifiers, and with the co-occurring noun categories that select each numeral classifier. Differently from KorLex of other POS, of which the structure depends largely on their reference model (Princeton WordNet), KorLexClas 1.0 and its extended version 1.5 adopt a direct building method. They demand a considerable time and expert knowledge to establish the hierarchies of numeral classifiers and the relationships between lexical items. For the efficiency of construction as well as the reliability of KorLexClas 1.5, we use following processes: (1) to use various language resources while their cross-checking for the selection of classifier candidates; (2) to extend the list of numeral classifiers by using a shallow parsing techniques; (3) to set up the hierarchies of the numeral classifiers based on the previous linguistic studies; and (4) to determine LUB(Least Upper Bound) of the numeral classifiers in KorLexNoun 1.5. The last process provides the open list of the co-occurring nouns for KorLexClas 1.5 with the extensibility. KorLexClas 1.5 is expected to be used in a variety of NLP applications, including MT.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.10
• /
• pp.6527-6533
• /
• 2015

It is generally accepted that there are differences between men and women in linguistic communication style. Genderlect is a socio-linguistic term to refer to the linguistic differences spoken by specific gender. Some linguistic features are provided as evidence to show the genderlects: pitch, lexicon, intonation, grammar and styles. The purpose of this paper is to compare the characteristics of genderlect in English and Korean. To do so, I analyzed the scripts of an English movie, 'Mrs. Doubtfire' and Korean tv drama, 'Oohlala couple'. In "Mrs. Doubtfire, tension and laughter arose out of discrepancy from the way he looked (as a woman) and the way he spoke (like a man). The same is true with "Oohlala couple." In the language of Mrs. Doubtfire, male speech characteristics with nouns were salient while in "Oohlala couple" with verb forms, especially with honorific style, which shows a difference between Korean and English genderlect. Korean language has special genderlect characteristics with honorific speech style realized in verb endings. In Korean the highest honorific speech style, 'Habsho-che' is used in official situation and men are more accustomed to it than women. When women have to use polite expressions they have to choose between the highest honorific style, 'Habsho-che' losing the female characteristics or the second highest honorific style 'Haeyo-che' keeping the female characteristics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.10
• /
• pp.19-26
• /
• 2006

In this study, psychological assessment was carried out to investigate the driver's psychological characteristics by the change of the headlight. The participants were 20 men and 20 women in their 20s and thirty-two different conditions in combinations of waveform of light, voltage, and alteration time were used. The questionnaire for the assessment was evaluated by 8 subjective item and 5-point SD criteria of 19 pair's adjective. The results were as follows : 1. The assessment results from SD method indicated 4 factors by factor analysis, and it was shown that A waveform had significances in a sense of security and impetus and B waveform had a significance in a sense of security. The levels of the limitations for the voltage change were 12[V] in the factor of a sense of security and 11[V] in the factor of a sense of impetus for A waveform, 12.6[V] in the factor of a sense of security for B waveform. 2. The results of the subjective assessment showed that the limitation of A waveform's brightness change was 12[V]. Moreover, the limitations of voltage changes were 12.67[V] for B waveform brightness change, 12.12[V] for discomfort, 12.71[V] for darkness. And the limitation of C waveform's brightness change was 12[V].

• Information Systems Review
• /
• v.23 no.4
• /
• pp.45-67
• /
• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.97-113
• /
• 2016

Due to the growth of internet data and the rapid development of internet technology, "big data" analysis is actively conducted to analyze enormous data for various purposes. Especially in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of existing structured data analysis. Various studies on sentiment analysis, the part of text mining techniques, are actively studied to score opinions based on the distribution of polarity of words in documents. Usually, the sentiment analysis uses sentiment dictionary contains positivity and negativity of vocabularies. As a part of such studies, this study tries to construct sentiment dictionary which is customized to specific data domain. Using a common sentiment dictionary for sentiment analysis without considering data domain characteristic cannot reflect contextual expression only used in the specific data domain. So, we can expect using a modified sentiment dictionary customized to data domain can lead the improvement of sentiment analysis efficiency. Therefore, this study aims to suggest a way to construct customized dictionary to reflect characteristics of data domain. Especially, in this study, movie review data are divided by genre and construct genre-customized dictionaries. The performance of customized dictionary in sentiment analysis is compared with a common sentiment dictionary. In this study, IMDb data are chosen as the subject of analysis, and movie reviews are categorized by genre. Six genres in IMDb, 'action', 'animation', 'comedy', 'drama', 'horror', and 'sci-fi' are selected. Five highest ranking movies and five lowest ranking movies per genre are selected as training data set and two years' movie data from 2012 September 2012 to June 2014 are collected as test data set. Using SO-PMI (Semantic Orientation from Point-wise Mutual Information) technique, we build customized sentiment dictionary per genre and compare prediction accuracy on review rating. As a result of the analysis, the prediction using customized dictionaries improves prediction accuracy. The performance improvement is 2.82% in overall and is statistical significant. Especially, the customized dictionary on 'sci-fi' leads the highest accuracy improvement among six genres. Even though this study shows the usefulness of customized dictionaries in sentiment analysis, further studies are required to generalize the results. In this study, we only consider adjectives as additional terms in customized sentiment dictionary. Other part of text such as verb and adverb can be considered to improve sentiment analysis performance. Also, we need to apply customized sentiment dictionary to other domain such as product reviews.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.6
• /
• pp.1077-1085
• /
• 2017

Urban space is a place that shows the behavior, experience and lifestyle of residents. Also by the combination of local attributes and assets, creating a space that reflects the unique image of the city. For the development of the city, it is important to actively reflect the identity of the space created by the difference of each space. In this study, we focused on the disparate of space and found the characteristics of urban space. And psychological factors on disparate images of the spatial analysis. As a result, 14 spatial image characteristics of Busan showed difference. In terms of dimensions, it could be classified as an natural, artificial, dynamic, static images. Also, the preference cluster of individuals showed a positive response in naturalness, openness, gentle slope and static space.

• Journal of Korean Society of Forest Science
• /
• v.103 no.3
• /
• pp.473-482
• /
• 2014

The objective of this study was to understand the effects of soundscapes on forest landscape preference in the Baekdudaegan protected area. The study sites were selected in Jeombongsan and Sobaek National park selected within the Baekdudaegan. The landscape preference surveys were conducted by using landscape adjectives classified with Nature, Sound, Attractiveness, and Aesthetics. The comparative analyses examined the difference of preferences between only visual landscapes and visual landscapes with soundscapes. The research found out that soundscapes were associated with landscape characteristics, and positively correlated with the improvement in landscape preference. Thus, the research can infer that forest landscape assessment consider visual attributes as well as soundscape cues.

• Management & Information Systems Review
• /
• v.39 no.2
• /
• pp.181-193
• /
• 2020

This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.1
• /
• pp.19-30
• /
• 2021

This research studied the effect of visual improvement of "72 Hour Project" that has regenerated small scale derelict spaces in Seoul through citizen participation. 29 projects built form 2016 to 2019 were analyzed. The research analyzed landscape image preference of before and after status of projects using 12 pairs of landscape adjectives. Basic statistical analysis, correlation analysis, factor analysis, cluster analysis, and ANOVA were performed based on the survey results. Since the satisfaction level of the projects compared with the before-condition was 3.63 higher than 3.00, it could be concluded that there was an meaningful effect of visual improvement after completion of the projects. As the result of the factor analysis, landscape adjective pairs were categorized into two factors: harmony and aesthetics. Through the cluster analysis, four clusters were formed and characteristics of each cluster were identified. As the result of rhe cluster analysis, the cluster with the high harmony level and the aesthetics level showed the highest overall satisfaction level. Comparing each cluster, it could be concluded that the factor of harmony was more important than the factor of aesthetics in evaluating the satisfaction level of projects. Analyzing qualitative aspects of project groups, spatially well-balanced design with generous vegetation areas was more effective in landscape improvement than artistic design with visually strong installations. Further researches based on behavior studies of actual users are required to compensate the limits of this research. This research can contribute to establish the improved direction of policies to regenerate various types of small scale derelict spaces.