• Proceedings of the KSPS conference
• /
• 2007.05a
• /
• pp.91-94
• /
• 2007

This paper aims to analyze the pronunciation of Korean Point-of-Interest (POI) data, which consist of 224 sound files, from the phonological point of view, adapting the notion of prosodic word within the framework of Intonational Phonology. Each POI word is broken down into prosodic words, which are defined as the minimal sequence of segments which can be produced as one Accentual Phrase (AP). Then the pronunciation of the POI word considering its prosodic words are analyzed. The results show that: in most cases, a prosodic word is realized as one AP; that, in some cases, two prosodic words are pronounced as one AP: and that no cases are found where 3 prosodic words are realized as one AP.

• Journal of KIISE:Software and Applications
• /
• v.34 no.2
• /
• pp.104-111
• /
• 2007

This paper examines how the performance of an automatic speech recognizer was improved for Korean Point-of-Interest (POI) data by modeling pronunciation variation using structural prosodic information such as prosodic words and syllable length. First, multiple pronunciation variants are generated using prosodic words given that each POI word can be broken down into prosodic words. And the cross-prosodic-word variations were modeled considering the syllable length of word. A total of 81 experiments were conducted using 9 test sets (3 baseline and 6 proposed) on 9 trained sets (3 baseline, 6 proposed). The results show: (i) the performance was improved when the pronunciation lexica were generated using prosodic words; (ii) the best performance was achieved when the maximum number of variants was constrained to 3 based on the syllable length; and (iii) compared to the baseline word error rate (WER) of 4.63%, a maximum of 8.4% in WER reduction was achieved when both prosodic words and syllable length were considered.

• Journal of Digital Convergence
• /
• v.13 no.12
• /
• pp.161-169
• /
• 2015

Realtime search words of typical portal sites appear every few seconds in descending order by search frequency in order to show issues increasing rapidly in interest. However, the characteristics of realtime search words reordering within too short a time cause problems that they go over the key issues of the day. This paper proposes a method for deriving a key issue through association analysis of realtime search words. The proposed method first makes scores of realtime search words depending on the ranking and the relative interest, and derives the top 10 search words through descriptive statistics for groups. Then, it extracts association rules depending on 'support' and 'confidence', and chooses the key issue based on the results as a graph visualizing them. The results of experiments show that the key issue through association rules is more meaningful than the first realtime search word.

• Korean Journal of Clinical Pharmacy
• /
• v.25 no.1
• /
• pp.27-33
• /
• 2015

Background: Since November 2012, some of over-the-counter (OTC) medications have been sold in convenience store without pharmacist' s supervision. We purposed to examine if the product labels of OTCs provide sufficient information that is appropriate for consumers who may have low health literacy. Methods: We compared the difficulty of words that are utilized in pharmaceutical product labels of interest (intervention) with those in the $6^{th}$ grade textbook (control). Pharmaceutical products of interest were comprised of 13 OTCs which have been sold currently in convenience stores. We grouped words into the 4 levels of difficulty based on the Korean Vocabulary Classification for Education, and statistically tested words frequency in each level between OTCs and control. Results: The 13 OTC labels included lay language (easier or equal to language used in primary school) about 10% less; professional language about 10% more (p < 0.001 in all). Labels for analgesics had the longest and most difficult information, followed by common cold preparations, muscle pain relievers as plaster or cataplasma and digestives. Conclusion: The 13 OTC labels might fail to provide appropriate information for safety use by consumers in terms of the difficulty level of words. The improvement of labels of OTC medications and consumer education strategies are called for safety use of OTC medications sold in convenience stores.

• Smart Media Journal
• /
• v.11 no.8
• /
• pp.73-83
• /
• 2022

In order to support new construction engineering companies with weak information power to successfully advance into the overseas construction market, this study tried to analyze what are the keywords of interest in the overseas construction market and how they differ from Korea. For this purpose, we recently collected 2,473 news article titles and major articles targeting smart cities that are of high interest in Korea and Vietnam. Through network configuration and topic modeling, we examined the connection relationship between the word of interest and the word of interest. In addition, the influence of the word of interest in the network was measured using PageRank centrality. Through this analysis, it was found that there is a high interest in smart city-related construction, cities, and digital in both countries, and the difference in terms of interest between Korea and Vietnam was inferred. Finally, the limitations of this study and additional research directions to complement them are presented.

• Science of Emotion and Sensibility
• /
• v.15 no.1
• /
• pp.105-120
• /
• 2012

This study aimed to develop a Korean emotion vocabulary list that functions as an important tool in understanding human feelings. In doing so, the focus was on the careful extraction of most widely used feeling words, as well as categorization into groups of emotion(s) in relation to its meaning when used in real life. A total of 12 professionals (including Korean major graduate students) partook in the study. Using the Korean 'word frequency list' developed by Yonsei University and through various sorting processes, the study condensed the original 64,666 emotion words into a finalized 504 words. In the next step, a total of 80 social work students evaluated and classified each word for its meaning and into any of the following categories that seem most appropriate for inclusion: 'happiness', 'sadness', 'fear', 'anger', 'disgust', 'surprise', 'interest', 'boredom', 'pain', 'neutral', and 'other'. Findings showed that, of the 504 feeling words, 426 words expressed a single emotion, whereas 72 words reflected two emotions (i.e., same word indicating two distinct emotions), and 6 words showing three emotions. Of the 426 words that represent a single emotion, 'sadness' was predominant, followed by 'anger' and 'happiness'. Amongst 72 words that showed two emotions were mostly a combination of 'anger' and 'disgust', followed by 'sadness' and 'fear', and 'happiness' and 'interest'. The significance of the study is on the development of a most adaptive list of Korean feeling words that can be meticulously combined with other emotion signals such as facial expression in optimizing emotion recognition research, particularly in the Human-Computer Interface (HCI) area. The identification of feeling words that connote more than one emotion is also noteworthy.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.16 no.4 s.44
• /
• pp.379-391
• /
• 1992

This study was intended to identify the constructing factors and the evaluative dimensions of clothing images. A questionnaire consisted of 110 words expressing clothing images was developed, and eight clothing photographs were selected as stimuli. 298 female subjects aged between 22 to 37 responsed to the 110 words for two photographs during September in 1991. After survey, 110 words were reduced to 62 words based on their independence, then factor analysis was conducted. As a result of factor analysis,6 factors-grace, modernity, unattractive- ness, activeness, dressiness, and youthfulness were found out as constructing factors of clothing images. One additional interest was the effect of design line to the formation of clothing images. ANOVA identified that curved line designs were perceived to be more graceful, modern, dressy, and youthful, and straight line designs were perceived to be more unattractive and active. The other interest was the effect of image factors to the total evaluation. So, regression was used. Consequently, the most influential factor to the total evaluation was found out as grace, followed by unattractiveness, modernity, youthfulness and activeness in a descending order. To identify the evaluative dimensions of clothing images, nine words of unattractiveness image factor were eliminated, and multidimensional scaling analysis was employed. Here, three dimensions were judged to be appropriate to explain the result. The first dimension in the multidimensional space was the evaluation in 'mannish image versus feminine image'. The second was the evaluation in 'simple image versus decorative image'. The third was the evaluation in 'pastoral image versus urbane image'.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.5
• /
• pp.385-392
• /
• 2002

Collaborative filtering method for personalization can suggest new items and information which a user hasn t expected. But there are some problems. Not only the steps for calculating similarity value between each user is complex but also it doesn t reflect user s interest dynamically when a user input a query. In this paper, classifying users by their interest makes calculating similarity simple. We propose the a1gorithm for readjusting user s interest dynamically using the profile and Bayesian learning. When a user input a keyword searching for a item, his new interest is readjusted. And the user s profile that consists of used key words and the presence frequency of key words is designed and used to reflect the recent interest of users. Our methods of adjusting user s interest using the profile and Bayesian learning can improve the real satisfaction of users through the experiment with data set, collected in University s library. It recommends a user items which he would be interested in.

• Journal of Oral Medicine and Pain
• /
• v.48 no.4
• /
• pp.137-143
• /
• 2023

Purpose: To assess Google Trends (GT) search behavior regarding orofacial pain (OFP) and headaches. Methods: GT scores for OFP and headache specialists between February 2013 and December 2022 were analyzed. Statistical tests such as Poisson regression analyses, mean differences, and Cohen's D were used to assess the score change over time. Results: The top three search words for OFP specialists were "temporomandibular joint (TMJ) specialist," "TMJ doctor," and "TMJ dentist," whereas the top three search words for headache specialists were "Headache specialist," "Headache doctor," and "Migraine specialist." Here, TMJ is temporomandibular joint. The GT scores for OFP specialists increased significantly (p<0.05) for all years except 2017, with the highest mean difference in 2020. The scores for headache specialists showed similar trends but gradually. Conclusions: The interest in OFP and headache specialists expressed by Google searches has increased over the years. More awareness is needed regarding the OFP scope of practice, and the use of GT may serve as an indicator.

• JOURNAL OF ELECTRICAL WORLD
• /
• no.3 s.8
• /
• pp.18-22
• /
• 1976

This essay will introduce that how the Korean and Japanese numerals have been developed from the same ancient original words. It would be a big interest for many people who have interested in knowing the origin of Japanese language of which many Japanese