• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.44-48
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• 2004

This paper proposes a phrase-based indexing system based on the phrase. the larger syntax unit than a single keyword. Early information retrieval systems with indexing system matching single keyword is simple and popular. But with single keyword matching it is very hard to represent the exact meaning of documents and the set of documents from retrieval is very large, therefore it can't satisfy the user of the information retrieval systems. Web documents include lots of syntactic errors, the natural language parser with high quality cannot be expected in Web. Partial trees, even not a full tree, from fully bottom-up parsing is still useful for extracting phrases, and they are much more discriminative than single keyword for index. It helps the information retrieval system enhance the efficiency and reduce the processing overhead, too.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.999-1006
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• 2022

The use of appropriate fonts is not only an aesthetic point of view, but also a factor influencing the reinforcement of meaning. However, it is a difficult process and wastes a lot of time for general users to choose a font that suits their needs and emotions. Therefore, in this study, keywords and fonts to be used in the experiment were selected for emotion-based font recommendation, and keyword values for each font were calculated through an experiment to check the correlation between keywords and fonts. Using the experimental results, a prototype of a keyword-based font recommendation system was designed and the possibility of the system was tested. As a result of the usability evaluation of the font recommendation system prototype, it received a positive evaluation compared to the existing font search system, but the number of fonts was limited and users had difficulties in the process of associating keywords suitable for their desired situation. Therefore, we plan to expand the number of fonts and conduct follow-up research to automatically recommend fonts suitable for the user's situation without selecting keywords.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.305-318
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• 2024

Purpose - The purpose of this study was to conduct a preliminary study to identify key trends on research articles indexed in KCI in relation to tourism in Jeju and sports tourism. Design/methodology/approach - Information regarding research articles focused on Jeju tourism and sports tourism indexed in KCI (145 and 120 articles respectively) were collected and finally abstract written in Korean of 100 and 91 articles on sports tourism and Jeju tourism respectively were chosen for the further analysis after removing redundant articles. R program was used to analyze keyword frequencies, co-occurring terms, and degree/betweeness centrality measures and visualize the keyword network results. Findings - Event, marketing, content, program, implication, service, stadium, and tourism destination have been identified as keywords with highest frequencies among research on sport tourism, whereas tourism destination, image, brand, content, data, Chinese, satisfaction, eco-tourism service, place of arrival were highly appearing terms among research on Jeju tourism. Research implications or Originality - This study highlighted that Jeju has been interlinked with a range of terms such as programs influencing Jeju tourism, natural environment, tourism-related resources (e.g., museums, dramas, etc.), whereas sports has been closely related to sports event and vaiours types of sports (e.g., bicycle, staking, and scuber), but not to Jeju-do.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.221-227
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• 2012

This research is a key words analysis on Radio Frequency Identification. Key words were collected from Korean research papers in the electronic library DBpia. 700 papers published from 2001 to 2011 were included. The number of collected key words is 1460. The trend of publishing research papers was increased rapidly from 2005, reached peak at 2009 and decreased after 2010. Majority of key words were related to hardware, information technology and standardization. Selected 128 key words were analyzed and clustered by social network analysis to find a relationship among key words on RFID.

• Journal of Korea Technology Innovation Society
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• v.8 no.2
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• pp.860-885
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• 2005

This study relates to develop a quantitative method through which promising technology-based business items can be discovered and selected. For this study, we utilized patent trend analysis, technology-industry concordance analysis, and keyword co-occurrence analysis of US patents. By analyzing patent trends and technology-industry concordance, we were able to find out the emerging industry trends : prevalence of bio industry, service industry, and B2C business. From the direct and co-occurrence analysis of newly discovered patent keywords in the year, 2000, 28 promising business item candidates were extracted. Finally, the promising item candidates were prioritized using 4 business attractiveness determinants; market size, product life cycle, degree of the technological innovation, and coincidence with the industry trends. This result implicates that reliable discovery and selection of promising technology-based business items can be performed by a quantitative, objective and low- cost process using knowledge discovery method from patent database instead of peer review.

• Korean Journal of Mathematics
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• v.29 no.4
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• pp.649-664
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• 2021

There have been numerous efforts to provide legal information to the general public easily. Most of the existing legal information services are based on keyword-oriented legal ontology. However, this keyword-oriented ontology construction has a sense of disparity from the relationship between the laws used together in actual cases. To solve this problem, it is necessary to study which laws are actually used together in various judicial precedents. However, this is difficult to implement with the existing methods used in computer science or law. In our study, we analyzed this by using topological data analysis, which has recently attracted attention very promisingly in the field of data analysis. In this paper, we applied the the Mapper algorithm, which is one of the topological data analysis techniques, to visualize the relationships that laws form organically in actual precedents.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.425-434
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• 2007

The sponsored search has become significant channel of online advertising, and the large sized advertisers have appeared, so the sponsored search strategy is becoming more important. Since CPC(Cost-per-Click) advertising has different price according to keyword, it is difficult to manage the a lot of keywords at one time. So, the purpose of this study is to investigate the factors which influence on the cost-per-click of sponsored search advertising. That is, there are four factors: impression, CTR(Click through Rate), conversion rate, and keyword's length. for the regression analysis, we use the actual data which is gotten from an ad agency. The result of that, the impression and keyword's length influence cost-per-click positively. However, CTR & conversion rate have no influence on it unexpectedly.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.227-233
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• 2016

Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.311-314
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• 2018

최근 '미투운동'이 활발히 진행되면서 새로운 페미니즘의 물결을 맞이하였다. 이전의 페미니즘 운동과의 차이점은 SNS 를 통해 익명으로 활동하며 전파속도가 굉장히 빠르다는 것이다. 본 연구는 미투운동의 이러한 특성을 고려하여 실제 트위터 데이터에서 주요 키워드를 파악하고, 해당 키워드의 연관성 및 네트워크 분석으로 사회적 맥락을 알아본다.

• 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.