• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.707-723
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• 2016

The purpose of this study is to focus on the effects of different channel types of Word-of-Mouth on the product attitude. Additionally, the product involvement and gender are considered as moderating variables. The results of this study show that different word-of-mouth channel types have different effects on the product attitude, that is, off-line has more influence than on-line does. Also the product involvement moderates the relationship between the channel types of word-of-mouth and the product attitude, while the gender does not. The results imply that while building the word-of-mouth marketing strategy, companies should not only pay attention to the on-line media channel, but lay importance on the off-line communication channel.

• Culinary science and hospitality research
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• v.9 no.3
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• pp.197-211
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• 2003

It is widely agreed that customers' purchase are strongly influenced by their emotions. despite the obvious importance of eliciting positive emotional responses from customers, we find no record that family restaurants have ever measured or used customers' emotions as a management tool. This study aimed to verify the importance of the customers' emotion in the relational performance of family restaurant business. In order to achieve the object of the study, the effect of emotional factors on service satisfaction, revisit, word-of-mouth were analysed. The data were collected from 450 customers who had visited five family restaurants in Seoul more than once during the last three months from September 20 to October 5, 2002. Emotional variables in service experience process were grouped as three factors; in the middle of having food, in entering and leaving restaurant and in the waiting line. It is proved that customers had different emotions in each process of family restaurant service experience. Multiple regression analysis was employed to explore the influence of three emotional factors on relational performances such as satisfaction, revisit and word-of-mouth. It was found that customers were influenced by emotional factors in entering and leaving restaurant, secondly influenced in the waiting line and least influenced in the middle of having food. Finally, the findings indicated that customers' emotional factors in whole service experience process from entering to leaving the restaurant should be successfully cared by service staff. Future research is recommended to find out which specific emotional factors affected on relational performance of family restaurant.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.139-149
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• 2013

As the importance of technology forecasting while countries and companies manage the R&D project is growing bigger, the methodology of technology forecasting has been diversified. One of the forecasting method is patent analysis. This research proposes quick forecasting process of emerging technology based on keyword approach using text mining. The forecasting process is following: First, the term-document matrix is extracted from patent documents by using text mining. Second, emerging technology keyword are extracted by analyzing the importance of word from utilizing mean values and standard deviation values of the term and the emerging trend of word discovered from time series information of the term. Next, association between terms is measured by using cosine similarity. finally, the keyword of emerging technology is selected in consequence of the synthesized result and we forecast the emerging technology according to the results. The technology forecasting process described in this paper can be applied to developing computerized technology forecasting system integrated with various results of other patent analysis for decision maker of company and country.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2089-2094
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• 2017

Altmetrics is the measurement index and quantitative data to complement the traditional indicators based on the citation. Altmetrics research has acquired greater importance in the past few years, partly due to the complement to the traditional bibliometrics. This paper aims to reveal the research status and trends in altmetrics research. A total of 187 articles from 2005 to 2017 are obtained and analyzed, illustrating a steady rise (S-mode) in altmetrics research since 2005. Using social network analysis and co-word analysis, the author cooperation network and keyword co-occurrence network are developed. The core scientists and eight international research groups are discovered, reflecting that researchers in this field have a low degree of cooperation. Four topics of altmetrics research are discovered by hierarchical clustering. The results can be useful for the advanced research of altmetrics.

• Journal of Korean Elementary Science Education
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• v.29 no.4
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• pp.401-413
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• 2010

This study analyzed the kinds and frequencies of descriptors in 154 articles in ERIC data base on the 4th day of January in 2010. The titles of the articles includes the words, 'scientific literacy'. As each descriptor is constituted of two words and over, in this study the first word in the descriptor was defined as 'restrictive word' and the rest word(s) as 'target word(s)'. The results are as follows. First, the descriptors which show high frequencies of target words are the traditionally important themes of scientific literacy education. Target words which show relatively high frequency are 'education', 'literacy', 'instruction' and 'countries'. Low frequency word is 'curriculum', which has various restrictive words and represents wide differentiation. Second, among the descriptors which show low frequencies of target words, relatively high frequency descriptors are '(and)society', 'change', 'secondary education', 'concepts', and 'biology', which have been given more attention in scientific literacy research than the rest descriptors. Third, the number of the descriptors that shows largely distributed pattern A, which happens over 15 years continuously, is over the half of all analyzed descriptors, which shows that they have been the major objectives in researches about scientific literacy. Most descriptors of pattern A shows normal distribution of frequency or the trends of increasing frequency as the time is nearer. Fourth, The descriptors are divided into four groups according to the time span. Each research trends are as follows. In later 80s, the research which emphasizes the importance of the sociality and technology in all level school science curriculum. In later 90s the research for educational change of inquiry-centered science curriculum which considers technological literacy in social contexts. In earlier 2000s the research that scientists and science teachers develop science curricula mostly related to scientific principles and thinking in chemistry and biology especially. In later 2000s case studies which relates teaching methods and science process activities to students' attitudes, scientific concepts and curricula.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.43-48
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• 2019

While reading text-only documents and finding unknown words, readers will become the focus disturbed and not be able to understand the content of the documents. Because children have little experience, it is difficult to understand correctly if the description in context is unfamiliar or ambiguous. In this paper, in order to help understand the text and increase the interest of the readers, we analyze the texts of documents and select the contents that are considered important, and implement a system that displays the most relevant images automatically from the web and links the texts and the images together. The implementation of the system divides the article into paragraphs, analyzes the text, selects important sentences for each paragraph and the important words that best represent the meaning of the important sentences, searches for images related to the words on the web, and then links the images to each of the previous paragraphs. Experiments have shown how to select important sentences and how to select important words in the sentences. As a result of the experiment, we could get 60% performance by evaluating the accuracy of the relation between three selected images and corresponding important sentences.

• The Research Journal of the Costume Culture
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• v.17 no.5
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• pp.911-922
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• 2009

As more consumers shop online and prefer private label apparel products, the importance of private label apparel brand of Internet shopping malls are increasing. This study investigated consumer attitudes toward private label apparel brand of Internet shopping malls. Attitudes were conceptualized into two sub-factors: utilitarian and hedonic. Based on findings of prior studies, subjective norm and familiarity were included as antecedents to attitude variables. Purchase intention and word of mouth intention were also included as consequence variables of attitudes. Types of Online shopping malls were considered as moderating variable. For the empirical research, the Online survey was conducted. Young male and female consumers who have experience in Internet shopping of clothing products participated in the study. 429 questionnaire were used for the final statistical analysis. Results indicated that subjective norm had significant influence on consumer attitudes toward private label apparel brand. Familiarity however did not have significant influence on attitude variables for general internet shopping malls. For specialized Internet shopping malls, familiarity had significant influence only on hedonic attitude. Attitude variables had significant influence on purchase intention and word of mouth intention. Subjective norm and familiarity had significant influence on purchase intention and word of mouth intention.

• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.129-147
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• 2004

This study is to investigate extensively the negative word-of-mouth responses and intentions of the public library users. It selects and analyzes empirically some of the antecedents of the complaining behaviors including severity of dissatisfaction attitude toward complaining, difficulty of the complaining, likelihood of success, product/service importance, external attributions, loyalty, and former experience of complaining. Final data through questionaries are obtained from 497 unsatisfied adult public library users in Taegu Metropolitan City, 443 of them analysed with SPSS 12.0 for Windows.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.129-142
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• 2018

Recently, the number of patent applications have been increasing rapidly every year as the importance of protecting intellectual property rights becomes more important. Patents must be inventive and have novelty. Especially, the novelty implies that the corresponding invention is not the same as the previous invention. To confirm the novelty, prior art search must be conducted before and after the application. The target of prior art search should include not only Korean patents but also foreign patents. Search of foreign patents should be supported by multilingual search techniques. However, a dictionary-based naive approach shows a limitation because some technical concepts are represented in different terms according to each nation. For example, a Korean term and a Japanese term may not be synonym even though they represent the same technical concept. In this paper, we propose a new method to map semantic similarity between technical terms in Korean patents and Japanese patents. To investigate different representations in each nation for the same technical concept, we identified and analyzed pairs of patents those are mutually connected with priority claim relationship. By performing an experiment with real-world data, we showed that our approach can reveal semantically similar technical terms in other language successfully.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.