• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.48-51
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• 2018

The traditional documents analysis was centered on words based system was implemented using a morpheme analyzer. These traditional systems can classify used words in the document but, cannot help to user's document understanding or analysis. In this problem solved, System needs extract for most valuable paragraphs what can help to user understanding documents. In this paper, we propose system extracts paragraphs of normalized XML document. User insert to system what filename when wants for analyze XML document. Then, system is search for keyword of the document. And system shows results searched keyword. When user choice and inserts keyword for user wants then, extracting for paragraph including keyword. After extracting paragraph, system operating maintenance paragraph sequence and check duplication. If exist duplication then, system deletes paragraph of duplication. And system informs result to user what counting each keyword frequency and weight to user, sorted paragraphs.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.115-140
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• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.49-63
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• 2015

Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.872-880
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• 2016

The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.143-150
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• 2019

This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.9-14
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• 2018

This study aims to investigate an importance of Author keyword with analysis the position of author keyword. An analysis was carried out on the position of author keyword. we examined an importance of Author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In the next stage, we performed analysis on correlation between network centrality measures and the position of keyword. As a result, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality both has a high value in 4th author keyword order. eigenvector centrality was the comparatively effective method to separate of author keyword order method than other 3 centrality. Correlation analysis result shows that the network analysis value are increasing in order. This study has significance in that it was able to examine the author keyword behavior. Future research is needed to identify and supplement future situational factors, behavior, and psychology.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.121-142
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• 2014

This study aims to investigate the importance of author keyword with analysis the position of author keyword in journal. In the first stage, an analysis was carried out on the position of author keyword. We examined the importance of author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality and effective size of structural hole. In the next stage, We performed analysis on correlation between network centrality measures and the position of author keyword. The result of correlation analysis on network centrality measures and the position of author keyword shows that there are the more significant areas of the result of the correlation analysis on degree centrality, betweenness centrality and the position of keyword. In addition, These results show that we need to consider that the possible way as measuring the importance of author keyword in journal is not only a term frequency but also degree centrality and betweenness centrality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.

• Journal of the Korean Society for information Management
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• v.21 no.2
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• pp.235-248
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• 2004

For the users of information retrieval systems, natural language query is the more ideal interface, compared with keyword and boolean expressions. This paper proposes a retrieval technique with expanded keyword from syntactically-analyzed structures of natural language query as user input. Through the steps combining or splitting the compound nouns based on syntactic tree traversal of the query, and expanding the other-formed or shorten-formed into multiple keyword, it can enhance the precision and correctness of the retrieval system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.4
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• pp.303-308
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• 2004

Natural language query is the best user interface for the users of information retrieval systems. This paper Proposes a retrieval system with expanded keyword from syntactically-analyzed structures of user's natural language query based on natural language processing technique. Through the steps combining or splitting the compound nouns based on syntactic tree traversal, and expanding the other-formed or shorten-formed keyword into multiple keyword, the system performance was enhanced up to 11.3% precision and 4.7% correctness.