• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.45-55
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• 2016

From 1970, the concept of ecotourism is introduced, lots of studies in ecotourism appeared. Review these studies are necessary for future ecotourism studies. Some review studies on ecotourism are existed. However, these approach also limitation of subjectivities and some sorts of papers has not been reviewed. This study use keyword network analysis which is used as big data analysis to overcome the limitation. Foreign 2455 studies and domestic 163 studies which have ecotoursim in keywords, are analyzed for reviewing. As a result, 3 cluster('Sustainable tourism development', 'Ecological conservation', 'Ecotourist analysis' appeared, in ecotourism studies. In addition, this cluster has deep relationship with region. 'Sustainable tourism development' is related to Eurasia, Australia, Europe. 'Ecological conservation' is related to Africa. 'Ecotourism analysis' is related to North America. Especially 'Resident participation', 'Stakeholder' are appeared many times in Asia region. These results show that ecotourism studies are interpreted in regional contexts. It means that although only one word 'ecotourism' is used in different contexts, regional approach are needed for exact use. In Korea, the keywords are focused on ecotourists and developments. As Korea has lots of ecotour village, resident participation studies have to be supplemented.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.41-46
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• 2022

The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.137-146
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• 2020

NLP means the technology that mechanically analyzes a language spoken by a human and makes it into a form that can be understood by a computer. This is important because it is a core technology for communication between humans and devices, which is the basis of artificial intelligence. In this paper, I analyzed patent information of US and Korea in order to identify technical trends related to NLP, especially semantic analysis. and the purpose of this study is to provide meaningful information for future research on NLP. In conclusion, the number of Korea patents is 7.9% compared to the USA and the different frequencies of the major keywords were found to differ from country to country in technical direction. In addition, the upward or downward keywords are twice as many in the U.S. as in Korea, and reflect the trend of the times relatively more. Based on these results, in future study, I will analysis how upward trending keywords are described in actual patents for concrete technology prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3937-3954
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• 2014

With the increasing electricity consumption and the wide application of renewable energy sources, energy auction attracts a lot of attention due to its economic benefits. Many schemes have been proposed to support energy auction in smart grid. However, few of them can achieve range query, ranked search and personalized search. In this paper, we propose an efficient multi-keyword range query (EMRQ) scheme, which can support range query, ranked search and personalized search simultaneously. Based on the homomorphic Paillier cryptosystem, we use two super-increasing sequences to aggregate multidimensional keywords. The first one is used to aggregate one buyer's or seller's multidimensional keywords to an aggregated number. The second one is used to create a summary number by aggregating the aggregated numbers of all sellers. As a result, the comparison between the keywords of all sellers and those of one buyer can be achieved with only one calculation. Security analysis demonstrates that EMRQ can achieve confidentiality of keywords, authentication, data integrity and query privacy. Extensive experiments show that EMRQ is more efficient compared with the scheme in [3] in terms of computation and communication overhead.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1393-1401
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• 2012

In this study, we pick graphene research as a case study to demonstrate the importance of follow-up monitoring the emerging technology items. Graphene was selected as an emerging technology from MIT(2008) and KISTEP(2009). We analyze the growth, transition, and differentiation of graphene research by keyword mapping techniques. Specifically, we investigate the changing aspects of biosensor area within graphene field to predict that it will be highly promising.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.609-611
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• 2014

Was developed of the web service in Due to the dissemination for IT skills development and smart appliances. In particular, Social network service for should be able to communicate feel free to a user across without distinguishing between production and consumption information in contrast to the existing web service. And strengthen to the information sharing relationships between existing human relation and new human relation. In this paper, a social network service in providing a social networking from users using their communication and information sharing is used to collect and analyze in the keyword. And a design of recommended system of movies for appropriate keyword.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.88-90
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• 2021

This paper introduces a method for extracting subtitles from lecture videos through a Korean morpheme analyzer and classifying video categories according to the extracted morpheme information. In some cases incorrect information is entered due to human error and reflected in the characteristics of the items, affecting the accuracy of the recommendation system. To prevent this, we generate a keyword table for each category using morpheme information extracted from pre-classified videos, and compare the similarity of morpheme in each category keyword table to classify categories of Lecture videos using the most similar keyword table. These human intervention reduction systems directly classify videos and aim to increase the accuracy of the system.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.277-285
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• 2007

This research proposes a personalized mobile web contents creation method that uses web news channel contents-based analysis. It promptly acquires data through the RSS and RSS-linked web pages which have been supplied by the existing web sites for a news search. And then It applies a personalization method using analysis in contents filtering and generation. The proposed method will make creating mobile web contents easier while lowering wireless contents production costs. Moreover, It can be improved a user satisfaction for contents filtering and access with using analysis that fits in with a matter of user's specific interest.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.115-124
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• 2013

In this study I selected the keyword analysis method to infer what's the components of production system. Magazine , were chosen, because they are most close media to production reality. After content analysis of , key words of main reports were programming production, institution policy, industry, technology. As for , institution policy, organization, programming production, collective action were frequently found. Even though there are some differences between two media, institution policy, industry, technology, organization keywords are very salient components regarding programming production.