• Title/Summary/Keyword: Key words

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Keyword identifications on dimensions for service quality of Healthcare providers (헬스케어 서비스 리뷰를 활용한 서비스 품질 차원 별 중요 단어 파악 방안)

  • Lee, Hong Joo
    • Knowledge Management Research
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    • v.19 no.4
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    • pp.171-185
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    • 2018
  • Studies on online review have carried out analysis of the rating and topic as a whole. However, it is necessary to analyze opinions on various dimensions of service quality. This study classifies reviews of healthcare services into service quality dimensions, and proposes a method to identify words that are mainly referred to in each dimension. Service quality was based on the dimensions provided by SERVQUAL, and patient reviews have collected from NHSChoice. The 2,000 sentences sampled were classified into service quality dimension of SERVQUAL and a method of extracting important keywords from sentences by service quality dimension was suggested. The RAKE algorithm is used to extract key words from a single document and an index is considered to consider frequently used words in various documents. Since we need to identify key words in various reviews, we have considered frequency and discrimination (IDF) at the same time, rather than identifying key words based only on the RAKE score. In SERVQUAL dimension, we identified the words that patients mentioned mainly, and also identified the words that patients mainly refer to by review rating.

A Statistical Study on the Key Words in the Titles of Nursing Related Theses (학위논문의 주요어 분석 (간호학 및 간호학관련 학위논문을 중심으로 : 1960-1991. 8))

  • 고옥자;김상혜;김희걸;이금재;이영숙
    • Journal of Korean Academy of Nursing
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    • v.24 no.1
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    • pp.58-69
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    • 1994
  • In order to see the development of Nursing related research activities in Korea over the last three decades, abstracts of almost all of the Master and Ph.D theses that appeared from 1961 up to August 1991 were collected. The number of theses was 2354, from which an index of key words has been constructed. Key words were defined as those terms in each thesis title that convey major objectives of the given thesis study and the important nursing concepts dealt with in the thesis. Although all the key words were picked from the thesis title only, full use was made of the abstracts in deciding the principal objectives and essential contents of the thesis studies and their important concepts as well. In total, 539 kinds of key words were identified from the 2354 titles, and the identified words were all found to be in the International Nursing Index. On an average each title has two key words. Which key words were most frequently used, how they have changed with time, what kind of concept is preferably dealt with by each graduate school, and the concepts to which a given key word is likely to be connected were examined. The results are summerized below : 1) For each decade the theses numbers were as follows : 54(2.3%) from the 60’s, 413(17.5%) from the 70’s, 1523(64.7%) from the 80’s, and 364(15.5%) from the 90’s. Master’s thesis contributed 96% (2252) of the papers and Ph. D’s theses filled the remaining 4%(102). 2) A total of 539 key words were used, averaging about 2 for each thesis. The most frequently used key words were ‘Nurse’, ‘Anxiety’, ‘Knowledge / Attitude /Practice’, ‘Stress /Stressor’, ‘Attitude’, ‘Job-Satisfaction’, ‘Mental Disorder’, ‘Operation’, ‘Elderly’, ‘Nursing Role’. 3) Each decades key words can be classified as : the 60’s : ‘Nursing Education’, ‘Pulmonary Tuberculosis’, ‘Mother-Child Health’, ‘Growth & Development’, ‘Public Facilities’, ‘Mental Disorder’ : the 70’s : ‘Nurse’, ‘Family Planning’, ‘Attitude’ / ‘Knowledge, Attitude / Practice’, ‘Curriculum in Nursing Education’, ‘Clinical Practice in Nursing’, ‘Analysis of the Work of the Nurse’, ‘Health Education of School’, : the 80’s : ‘Nurse’, ‘Anxiety’, ‘Stress /Stressor’, ‘Operation’, ‘Nursing Role’, ‘Job Satisfaction’ : the 90’s : ‘Nurse’, ‘Elderly’, ‘Family-Support’, ‘Stress /Stressor’, ‘Home Care’. Key word ‘Nurse’ appears continuously and most frequently through the years, which indicates that there has been active study of the characteristics of nurses and related fields. The concept ‘Anxiety’ has been studied steadly from the 80’s and it shows that interest in health and disease are increasing Which comes as a result of society changing to an industrial and informational community. 4) Looking into each graduate school’s study area key words ‘Anxiety’, ‘Nurse’, ‘Mental Disorder’, ‘Stress /Stressor’, ‘Operation’, ‘Attitude’, ‘Hemo-dialysis’, were studied in the regular graduate school : ‘Family Planning /Contraception’, ‘Knowledge / Attitude /Practice’, ‘Physical Health-State /Physical Health Examination’, ‘Nurse’, ‘Using Clinical Facilities’, ‘Health Education of School’, were studied in the Graduate School of Public Health’ ; ‘Nurse’, ‘Anxiety’, ‘Stress / Stressor’, ‘Job-Satisfaction’, ‘Clinical Practice Education’, ‘Nursing Education’, were studied in the Graduate School of Education : ‘Nurse’, ‘Job Satisfaction’, ‘Nursing Role’, ‘Administration - Employment /Employment Management’, ‘Leadership’, ‘Personnel Profile’, ‘Nursing Manpower / Changing Working Place’, were studied in the Graduate School of Public Administration. 5) The Connection between key words were : ‘Nurse Job Satisfaction’, ‘Stress / Stressor ⇔ Coping / Ajustment’, ‘Nurse ⇔ Nursing Role’, ‘Anxiety ⇔ Giving Information’, ‘Nurse ⇔ Stress / Stressor’, ‘Anxiety ⇔ Operation’, ‘Nurse ⇔ Burnout’, ‘Knowledge, Attitude, Practice ⇔ Family Planning’, ‘Nurse Administration ⇔ Employment’, ‘Anxiety Muscle ⇔ Relaxation Technic’, ‘Anxiety ⇔ Mental Disorder’. From the above it can be noted that many nursing concepts were handled in the thesis titles. But there were more than enough papers on the characteristics of the nurse. It is suggested that in depth research be made on ‘Nursing Accidents’, t-‘Ethics’, ‘Nurse - Patient Interactions’, ‘Spritual Care’, ‘Dying’, ‘Hospice’, ‘Resident Helper’ and that there should be in depth research relating to the physical and mental development of youth and in particular physical concepts like ‘Drug - Abuse’, ‘Child -Abuse and Teaching’.

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A Method of Chinese and Thai Cross-Lingual Query Expansion Based on Comparable Corpus

  • Tang, Peili;Zhao, Jing;Yu, Zhengtao;Wang, Zhuo;Xian, Yantuan
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.805-817
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    • 2017
  • Cross-lingual query expansion is usually based on the relationship among monolingual words. Bilingual comparable corpus contains relationships among bilingual words. Therefore, this paper proposes a method based on these relationships to conduct query expansion. First, the word vectors which characterize the bilingual words are trained using Chinese and Thai bilingual comparable corpus. Then, the correlation between Chinese query words and Thai words are computed based on these word vectors, followed with selecting the Thai candidate expansion terms via the correlative value. Then, multi-group Thai query expansion sentences are built by the Thai candidate expansion words based on Chinese query sentence. Finally, we can get the optimal sentence using the Chinese and Thai query expansion method, and perform the Thai query expansion. Experiment results show that the cross-lingual query expansion method we proposed can effectively improve the accuracy of Chinese and Thai cross-language information retrieval.

Exploring Major Keyword & Relationship in the Studies of Hotel Employees Using Semantic Network Analysis Methods

  • Kim, Jeong-O;Kwon, Choong-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.7
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    • pp.135-141
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    • 2019
  • The purpose of this study is to extract the key words from the list of research subjects related to 'hotel workers' published in recent 10 years(2009~2018) by using the language network analysis method and to confirm the relation between the key words. In this paper, we propose a semantic network analysis that can overcome limitations of longitudinal study, analyze the recent research trends, and widely use as a research model. The results of this study are as follows ; First, in analyzing major key words in the title of 'Hotel Employer' in recent 10 years, the major keyword of job satisfaction(40), special grade(26), organizational commitment(20), emotional labor(19), service(12), restaurant(10), and turnover intention(9). Second, we analyzed the relation of language network among major key words extracted from the study title of 'hotel workers'. Such a research process is expected to grasp the trends of research related to 'hotel workers' and give implications for the future direction of related research.

Can Similarities in Medical thought be Quantified? - Focusing on Donguibogam, Uihagibmun and Gyeongagjeonseo - (의학 사상의 유사성은 계량 분석 될 수 있는가 - 『동의보감』과 『의학입문』, 『경악전서』를 중심으로 -)

  • Oh, Junho
    • Journal of Korean Medical classics
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    • v.31 no.2
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    • pp.71-82
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    • 2018
  • Objectives : The purpose of this study is to compare the similarities among Donguibogam(DO), Uihagibmun(UI), and Gyeongagjeonseo(GY) in order to examine whether the medical thoughts embedded in the texts can be compared in a quantitative way. Methods : Under an empirical assumption that medical thoughts can be reduced to the frequency of major key words within the text, we selected the fourteen words of the four categories that are commonly used to describe physiology and pathology in Korean medicine as key words. And the frequency of these key words was measured and compared with each other in the three important medical texts in Korea. Results : As a result of quantitative analysis based on ${\chi}^2$ statistic, the key words in the books were distributed most heterogeneously in DO and distributed most homogeneously in UI. In comparison of the similarity analyzed by the same method, DO and UI were significantly more similar than those of DO and UI. The results of the word frequency pattern and the similarities of the book contents(CBDF) show that DO is influenced by UI, and the differences between standardized residuals and homogeneity tells us that internal context of both books are constructed differently. Conclusions : These results support the results of traditional research by experts. With the above, we were able to confirm that medical thoughts can be reduced to the frequency of major key words within the text, and compared through the frequency of such key words.

An analysis on the characteristics of digital life reflected in web sites (웹사이트에 나타난 디지털 라이프의 특성 분석)

  • 조명은;김현경;이현수
    • Journal of the Korean housing association
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    • v.12 no.2
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    • pp.181-190
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    • 2001
  • The purpose of this study is to analysis web sites which relate to housing environment on Internet and to suggest guidelines which are needed in digital life. Data are in 53 web sites searched by housing environmental word such as people, living, town and so on. The web sites are analyzed by key words. The results of this study were as follow: The web sites are divided into e-housing community, e-housing management, e-housing workplace and e-housing design. These are the digital life of new type. E-housing community sitess key words are 3D virtual world, chatting, information, service, community etc. E-housing community is related to making new wired community cross time and space. E-housing management sitess key words are guard management, apartment management, building management etc. E-housing management sites provide the useful information of housing management. E-housing workplace sitess key words are virtual office. conference etc. E-housing workplace sites enable us to work in cyberspace. E-housing design sitess key words are design, interior, furniture etc. E-housing design sites provide marketing, consulting and designing in relation to the house. The web life style on cyberspace is common and makes many changes happen in house life and environment.

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Classification of Keywords of the papers from the Journal of Korean Academy of Nursing Administration(2002-2006) (간호행정학회지 게재논문 주요어 분석(2002년${\sim}$2006년))

  • Seomun, Gyeong-Ae;Kim, In-A;Koh, Myung-Suk
    • Journal of Korean Academy of Nursing Administration
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    • v.13 no.1
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    • pp.118-122
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    • 2007
  • Purpose: This study was to understand the major subjects of the recent nursing research in Nursing administration from keywords. Method: Keywords of journals were extracted and the frequency of the appearance of each key words was sorted by a descending order. Results: A total of 327 key words were used. The most frequently used key words were 'Job satisfaction', 'Organizational commitment', 'Leadership'. Out of them, organizational culture, nursing performance, nursing classification, patient satisfaction, and ethics appeared most frequently in descending order. Conclusion: From the above it can be noted that many nursing administration concepts were handled in the papers. But there were not enough papers on the characteristics of the Nursing administration. It is suggested that in depth research be made on 'Nursing error', 'Nursing informatics', 'Web based learning'.

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Research trends in dental hygiene based on topic modeling and semantic network analysis

  • Yun-Jeong Kim;Jae-Hee Roh
    • Journal of Korean society of Dental Hygiene
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    • v.22 no.6
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    • pp.495-502
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    • 2022
  • Objectives: The purpose of this study was to analyze research trends in dental hygiene using topic modeling and semantic network analysis. Methods: A total of 261 published studies were collected 686 key words from the Research Information Sharing Service (RISS) by 2019-2021. Topic modeling and semantic network analysis were performed using Textom. Results: The most frequently and frequency-inverse document frequently key words were 'dental hygienist', 'oral health', 'elderly', 'periodontal disease', 'dental hygiene'. N-gram of key words show that 'dental hygienist-emotional labor', 'dental hygienist-elderly', 'dental hygienist-job performance', 'oral health-quality of life', 'oral health-periodontal disease' etc. were frequently. Key words with high degree centrality were 'dental hygienist (0.317)', 'oral health (0.239)', 'elderly (0.127)', 'job satisfaction (0.057)', 'dental care (0.049)'. Extracted topics were 5 by topic modeling. Conclusions: Results from the current study could be available to know research trends in dental hygiene and it is necessary to improve more detailed and qualitative analysis in follow-up study.

Analyzing Knowledge Structure of Defense Area using Keyword Network Analysis

  • Lee, Yong-Kyu;Yoon, Soung-Woong;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.10
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    • pp.173-180
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    • 2018
  • In this paper, we analyzed key keywords and research themes in the field of defense research using keyword network analysis and tried to grasp the whole knowledge structure. To do this, we extracted data from 2,165 research data from defense related research institutes from 2010 to 2017 and applied the Pareto rule to the number of abstracts of words and the number of links between words, We extracted a total of 2,303 words based on the criterion and extracted 204 final key words through component analysis. By analyzing the centrality and cohesiveness through these key words, we confirmed the concept of core research in the defense field and derived a total of 7 large groups and 16 small groups of each group in the knowledge structure of the defense area.

Selecting a key issue through association analysis of realtime search words (실시간 검색어 연관 분석을 통한 핵심 이슈 선정)

  • Chong, Min-Yeong
    • Journal of Digital Convergence
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    • v.13 no.12
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    • pp.161-169
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    • 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.