• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1176-1189
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• 1993

This paper presents the Multiple Keyword Retrieval Method under the Object-Oriented Multimedia Database Model. The multiple keyword registration and retrieval algorithms are developed to reduce the partial matching problem in multimedia data retrieval. For this, proper storage structures of the lookup tables are designed. And also, in order to maintain the constant retrieval time, media data files are organized with B+ tree structure.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.93-101
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• 2017

This study investigate the effect of each type of search volume on the number of Facebook fans and the number of tourists. According to the hierarchy effect model, the effect of communication appears to be the sequentiality of cognition-attitude-behavior. Applying this theory, this study predicted that when consumers who have higher involvement and knowledge on specific cities through search behavior, they will be more active in information search through Facebook fan page subscription and will lead to direct tourism behavior. To verify the prediction, we examined the influences among search volume of Seoul shown in Google Trend, the number of fans of official facebook page named 'Seoul Korea', and the number of foreign tourists. As a result, the type of search keyword was divided into four categories: tourism attraction keyword, natural environment keyword, symbolic keyword, and accessibility keyword. The regression analysis showed that tourism attraction keyword and symbolic keyword have influence on Facebook fanpage 'Like'. In addition, facebook fanpage fan size have mediation effect between search volume and number of tourists. All in all, it would be useful to appeal to foreign tourists with a message that emphasizes tourism attraction and Korea-related contents.

• Journal of the Korean Society for information Management
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• v.17 no.2
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• pp.139-153
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• 2000

This article focuses on a transaction log analysis of the DISCOVER online catalog user interface at Duksung Women's University Library. The results show that the most preferred access point is the title field with rate of 59.2%. The least used access point is the author field with rate of 11.6%. Keyword searching covers only about 16% of all access points used. General failure rate of searching is 13.9% with the highest failure rate of 19.8% in the subject field and the lowest failure rate of 10.9% in author field.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.580-585
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• 2006

본 논문에서는 대학생들의 프로그래밍 과제물이나 프로그래밍 경진대회에 제출된 프로그램과 같이 동일한 기능을 요구받는 프로그램 소스 집합들에서 표절 행위가 있었는지를 탐색하는 새로운 알고리즘을 제시한다. 본 논문에서는 프로그램의 소스 집합에서 추출된 키워드들의 빈도수에 기반한 로그 확률값을 가중치로 하는 적응적(adaptive) 유사도 행렬을 만들어 이를 기반으로 주어진 프로그램의 유사구간을 탐색하는 지역정렬(local alignment) 방법을 소개한다. 우리는 10여개 이상의 프로그래밍 대회에 제출된 실제 프로그램으로 본 방법론을 실험하였다. 실험결과 이 방법은 이전의 고정적 유사도 행렬(일치 +1, 불일치 -1, 갭(gap)을 이용한 일치 -2)에 의한 유사구간 탐색에 비하여 여러 장점이 있음을 알 수 있었으며, 보다 다양한 표절탐색 목적으로 제시한 적응적 유사도 행렬이 응용될 수 있음을 알 수 있었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.636-639
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• 2004

본 논문은 웹 도큐먼트를 기반으로 사용자에게 의미 있는 정보를 찾아주기 위한 연관 객체 추출 기법인 PMPL(Personalized Multi-Strategey Pattern Loaming) 시스템을 제안하고자 한다. PMPL 모듈은 인터넷의 정보를 여과하여 필터링하고, 사용자 개인화의 키워드를 중심으로 연관된 객체를 추출한다. 이때 연관된 객체 추출 시 대용량 데이터에서 시간적, 공간적면에서 효율적인 연관 탐색 기법인 Fp-Tree와 Fp-Growth 알고리즘을 적용시켰으며, 연관규칙 탐색을 보완하기 위해 가중치 기법인 만유인력 기법을 적용시켰다. PMPL 시스템을 실행한 결과 개인화된 사용자 중심어 기초로 기존의 단일 학습 기법에 비해 더 많은 의미 있는 연관 지식을 추출한 결과가 보였다.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.331-336
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• 2015

On the IoT-based sensor networks, users or sensor nodes must perform a Service Discovery (SD) procedure before access to the wanted service. Current approach uses a center-concentrated Resource Directory (RD) servers or P2P technique, but these can cause a point-of-failure or flooding of SD messages. In this paper, we proposes an improved SWoT SD approach for CoAP-based sensor networks, which integrates Social Web of Things (SWoT) concept to current CoAP-based SD approach that makes up for weak points of existing systems. This new approach can perform a function like a keyword or location-based search originated from SNS, which can enhances the usability. Finally, we implemented a real system to evaluate.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.249-265
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• 2023

Recently, the satellite industry has been paying attention to the private-led 'New Space' paradigm, which is a departure from the traditional government-led industry. The space industry, which is considered to be the next food industry, is still receiving relatively little attention in Korea compared to the global market. Therefore, the purpose of this study is to explore future signals that can help determine the market entry strategies of private companies in the domestic satellite industry. To this end, this study utilizes the theoretical background of future signal theory and the Keyword Portfolio Map method to analyze keyword potential in patent document data based on keyword growth rate and keyword occurrence frequency. In addition, news data was collected to categorize future signals into first symptom and early information, respectively. This is utilized as an interpretive indicator of how the keywords reveal their actual potential outside of patent documents. This study describes the process of data collection and analysis to explore future signals and traces the evolution of each keyword in the collected documents from a weak signal to a strong signal by specifically visualizing how it can be used through the visualization of keyword maps. The process of this research can contribute to the methodological contribution and expansion of the scope of existing research on future signals, and the results can contribute to the establishment of new industry planning and research directions in the satellite industry.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.169-178
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• 2017

In various research fields, it is important to identify the trends and meaningful patterns in large volumes of text data. We examined the research trends and patterns in global journal articles related to aviation and airlines from 1997 to 2016 using keyword network analysis. Keyword network models were constructed, and centrality (degree and betweenness) analysis was performed using 25,959 articles from the Scopus database. The results suggested that the recent research trends in aviation and airlines could be quantitatively described through keyword network analysis. The engineering and social science fields were the most relevant fields with keywords related to aviation and airlines. In addition, it was shown that betweenness centrality increased with the degree centrality of keywords. The results of this study could be applied to establish policies and suggest further research topics in the field of aviation and airlines based on empirical data.

• 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.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.163-182
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• 2019

Analyzing the frequency and correlation of the news keywords in the modern society that are becoming complicated according to the time flow is a very important research to discuss the response and solution to issues. This paper analyzed the relationship between the flow of social keyword and major issues through the analysis of news big data for 10 years (2009~2018). In this study, political issues, education and social culture, gender conflicts and social problems were presented as major issues. And, to study the change and flow of issues, it analyzed the change of the issue by dividing it into five years. Through this, the changes and countermeasures of social issues were studied. As a result, the keywords (economy, police) that are closely related to the people's life were analyzed as keywords that are very important in our society regardless of the flow of time. In addition, keyword such as 'safety' have decreased in increasing rate compared to frequency in recent years. Through this, it can be inferred that it is necessary to improve the awareness of safety in our society.