• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.29-36
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• 2010

Past clustering researches are focused on extraction of keyword for word similarity grouping. However, too many candidates to compare and compute bring high complexity, low speed and low accuracy. To overcome these weaknesses, this paper proposed a topical web document clustering model using not only keyword but also named entities such as person name, organization, location, and so on. By several experiments, we prove effects of our model compared with traditional model based on only keyword and analyze how different effects show according to characteristics of document collection.

• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.440-447
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• 2013

Recently corpus linguistic analyses enable researchers to examine meanings and structural features of data, that is not detected intuitively. While the potential of corpus linguistic techniques has been established and demonstrated for non-literary data, corpus stylistic analyses have been rarely performed in terms of the analysis of literature. Specifically this paper explores keywords and their role in text analysis, which is primary part of corpus linguistic analyses. This paper focuses on the application of techniques from corpus linguistics and the interpretation of results. This paper addresses the question of what is to be gained from keyword analysis by scrutinizing keywords in Shakespeare's Romeo and Juliet.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.3
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• pp.9-23
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• 2022

This study aims to examine research trends on the Internet of Things and smart city based on papers from the United States, Japan, and Korea. We collected 7113 papers related to the Internet of Things and smart city published from 2016 to 2021 in Elsevier's Scopus. Keyword frequency and centrality analysis were performed based on the abstracts of the collected papers. We found keywords with high frequency of appearance by calculating keyword frequency and identified central research keywords through the centrality analysis by country. As a result of the analysis, research on security, machine learning, and edge computing related to the Internet of Things and smart city were the most central and highly mediating research conducted in each country. As an implication, studies related to deep learning, cybersecurity, and edge computing in Korea have lower degree centrality and betweenness centrality compared to the United States and Japan. To solve the problem it is necessary to combine these studies with various fields. The future research direction is to analyze research trends on the Internet of Things and smart city in various regions such as Europe and China.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1075-1088
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• 2022

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.3
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• pp.103-110
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• 2008

This paper proposes an effective keyword extraction method for the Web videos. The proposed method classifies the Web video pages in one of 4 types. As such, we analyzed the structure of the Web pages based on the number of videos and the layout of the Web pages. And then we applied the keyword extraction algorithm fit to each page type. The experiment with 1,087 Web pages that have total 2,462 videos showed that the recall of the proposed extraction method is 18% higher than ImagerRover[2]. So, the proposed method could be used to build a powerful video search system for WWW.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.29-40
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• 2001

In this paper, we suggest a query optimization algorithm to select the optimal processing method of an extended boolean query on inverted files. There can be a lot of methods for processing an extended boolean query according to the processing sequence oh the keywords con tamed in the query, In this sense, the problem of optimizing an extended boolean query it essentially that of optimizing the keyword sequence in the query. In this paper, we show that the problem is basically analogous to the problem of finding the optimal join order in database query optimization, and apply the ideas in the area to the problem solving. We establish the cost model for processing an extended boolean query and develop an algorithm to filled the optimal keyword-processing sequence based on the concept of keyword rank using the keyword selectivity and the access costs of inverted file. We prove that the method selected by the optimization algorithm is really optimum, and show, through experiments, that the optimal method is superior to the others in performance We believe that the suggested optimization algorithm will contribute to the significant enhancement of the information retrieval performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.564-568
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• 2011

Microblogs became popular information delivery ways due to the spread of smart phones. They have the characteristic of reflecting the interests of users more quickly than other medium. Particularly, in case of the subject which attracts many users, microblogs can supply rich information originated from various information sources. Nevertheless, it has been considered as a hard problem to obtain useful information from microblogs because too much noises are in them. So far, various methods are proposed to extract and track some subjects from particular documents, yet these methods do not work effectively in case of microblogs which consist of short phrases. In this paper, we propose a graph-based topic extraction and partitioning method to understand interests of users about a certain keyword. The proposed method contains the process of generating a keyword graph using the co-occurrences of terms in the microblogs, and the process of splitting the graph by using a network partitioning method. When we applied the proposed method on some keywords. our method shows good performance for finding a topic about the keyword and partitioning the topic into sub-topics.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.45-50
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• 2020

The purpose of this study is to analyze relationships among essential keywords in curriculum. The number of 1,935 keyword was collected from 644 manuscripts published between 2002 and 2019. For data analysis, this study selected softwares of KrKwic and KrTitle to compose a 1-mode network matrix and UCINET 6 and NetDraw to implement network analysis and visualization. Results are as follows. First, the frequency of keyword was curriculum, curriculum development, national curriculum, competency-based curriculum, 2015 revised national curriculum, curriculum implementation, understanding by design, competency, teacher education, school curriculum, and IBDP from highest to lowest. Second, degree centrality was curriculum development, curriculum, competency-based curriculum, national curriculum, 2015 revised national curriculum, understanding by design, competency, key competency, high school curriculum, textbook, curriculum implementation, teacher education, and IBDP from highest to lowest.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1691-1697
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• 2003

The Internet is standing in the spotlight of a new medium of advertisement with explosive growth of market share of electronic commerce, several Internet advertising methods have been implemented. Among them, the banner advertising method is typically being used in the Internet, but the users are not willing to see the banner advertising, moreover that method shows low click rate. Accordingly we propose a new Internet advertising method that makes expose advertising content according to proper text keyword in the article of web pages. During user is reading a article of web page, when user puts mouse pointer over a text keyword, previously specified advertising content is appeared on the web page. The proposed method is based on the keyword advertising, and unlike banner advertising, various shape of images can be applied. Also whole web page could be used for advertising area, and the method does not affect loading delay time of web page.