• Information Systems Review
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• v.25 no.2
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• pp.125-144
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• 2023

Generative Artificial Intelligence (AI) technology is gaining global attention as it can automatically generate sentences, images, and voices that humans previously generated. In particular, ChatGPT, a representative generative AI service, shows proactivity and accuracy differentiated from existing chatbot services, and the number of users is rapidly increasing in a short period of time. Despite this growing interest in generative AI services, most preceding studies are still in their infancy. Therefore, this study utilized LDA topic modeling and keyword network diagrams to derive success factors for generative AI services and to propose successful business strategies based on them. In addition, using ChatGPT, a new research methodology that complements the existing text-mining method, was presented. This study overcomes the limitations of previous research that relied on qualitative methods and makes academic and practical contributions to the future development of generative AI services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.1
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• pp.17-29
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• 2024

The Gyeongin Ara Waterway is a regional development project designed to transport cargo by sea and to utilize the surrounding waterfront area to enjoy tourism and leisure. It is being used as a space for demonstration projects for urban air transportation (UAM), which has recently been attracting attention, and various efforts are being made at the local level to strengthen cultural and tourism functions and revitalize local food. This study examined the perception and trends of tourism consumers on the Gyeongin Ara Waterway before and after the outbreak of COVID-19. The research method utilized semantic network analysis based on social network analysis. As a result of the study, first, before the outbreak of COVID-19, key words such as bicycle, Han River, riding, Gimpo, Seoul, hotel, cruise ship, Korea Water Resources Corporation, emotion, West Sea, weekend, and travel showed a high frequency of appearance. After the outbreak of COVID-19, keywords such as cafe, discovery, women, Gimpo, restaurant, bakery, observatory, La Mer, and cruise ship showed a high frequency of appearance. Second, the results of the degree centrality analysis showed that before the outbreak of COVID-19, there was increased interest in accommodations for tourism, such as Marina Bay and hotels. After the outbreak of COVID-19, interest in food such as specific bakeries and cafes such as La Mer was found to be high. Third, due to the CONCOR analysis, five keyword clusters were formed before the outbreak of COVID-19, and the number of keyword clusters increased to eight after the outbreak of COVID-19.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.103-118
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• 2024

Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.

• Smart Media Journal
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• v.13 no.9
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• pp.9-17
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• 2024

This study aims to analyze the current status of smart tourism in various regions. To achieve this, 599 news articles containing the keyword 'smart tourism' were collected from national daily newspapers in the BigKinds database, covering the period from January 2014 to June 2024. The collected data was subject to topic modeling based on location, and network analysis was performed using the keyword frequencies in each topic. The topic modeling results identified six major topics: 'Jeju,' 'Incheon,' 'Daegu_Busan_Ulsan,' 'Gyeongju,' 'Suwon,' and 'Yangyang.' It was found that the development of smart tourism in all these regions is centered around tourism projects led by government and local authorities. The network analysis results revealed that 'platform' and 'content' are key keywords related to smart tourism technology across all topics, indicating that these concepts are interconnected to provide services to individual tourists. The findings of this study are expected to provide valuable information for formulating policies and strategies to promote smart tourism in various regions and contribute to the realization of sustainable smart tourism.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.189-199
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• 2017

Thisstudy quantitatively analyzed the research trendsin the use ofICT ofthe environmental field using the text mining technique. To that end, the study collected 359 papers published in the past two decades(1996-2015)from the National Digital Science Library (NDSL) using 38 environment-related keywords and 16 ICT-related keywords. It processed the natural languages of the environment and ICT fields in the papers and reorganized the classification system into the unit of corpus. It conducted the text mining analysis techniques of frequency analysis, keyword analysis and the association rule analysis of keywords, based on the above-mentioned keywords of the classification system. As a result, the frequency of the keywords of 'general environment' and 'climate' accounted for 77 % of the total proportion and the keywords of 'public convergence service' and 'industrial convergence service' in the ICT field took up approximately 30 % of the total proportion. According to the time series analysis, the researches using ICT in the environmental field rapidly increased over the past 5 years (2011-2015) and the number of such researches more than doubled compared to the past (1996-2010). Based on the environmental field with generated association rules among the keywords, it was identified that the keyword 'general environment' was using 16 ICT-based technologies and 'climate' was using 14 ICT-based technologies.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.395-408
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• 2004

A conjunctive Boolean text query refers to a query that searches for tort documents containing all of the specified keywords, and is the most frequently used query form in information retrieval systems. Typically, the query specifies a long list of keywords for better precision, and in this case, the order of keyword processing has a significant impact on the query speed. Currently known approaches to this ordering are based on heuristics and, therefore, cannot guarantee an optimal ordering. We can use a systematic approach by leveraging a database query processing algorithm like the dynamic programming, but it is not suitable for a text query with a typically long list of keywords because of the algorithm's exponential run-time (Ο(n2$^{n-1}$)) for n keywords. Considering these problems, we propose a new approach based on a property called the join sequence separability. This property states that the optimal join sequence is separable into two subsequences of different join methods under a certain condition on the joined relations, and this property enables us to find a globally optimal join sequence in Ο(n2$^{n-1}$). In this paper we describe the property formally, present an optimization algorithm based on the property, prove that the algorithm finds an optimal join sequence, and validate our approach through simulation using an analytic cost model. Comparison with the heuristic text query optimization approaches shows a maximum of 100 times faster query processing, and comparison with the dynamic programming approach shows exponentially faster query optimization (e.g., 600 times for a 10-keyword query).

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.91-110
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• 2021

In the face of the prolonged Covid-19, this study conducted a network analysis to propose the policy direction for the Korean National Assembly to go forward. Using COVID-19 news articles, various types of networks were created and analyzed for the parliamentary activities of the Korean National Assembly related to Covid-19. Specifically, we utilize the co-occurrence and keyword information to generate two types of parliamentary networks: co-occurrence-based network and content-based network. In addition, a topic keyword-driven parliamentary network was constructed by using topic modeling. The results of the study are as follows. First, lawmakers in the ruling party had a wide range of topics regarding Covid-19, while lawmakers from other political parties had a limited number of issues covered. Next, a few representative legislators were identified as influential actors in most of the centrality indicators. Based on the research results, cooperation on diverse agendas related to Covid-19 should be promoted between lawmakers from various political parties. And representative legislators from both major parties should play a crucial role as intermediaries to increase communication between them.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.428-435
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• 2016

Hundreds of millions of new posts and information are being uploaded and propagated everyday on Online Social Networks(OSN) like Twitter, Facebook, or Instagram. This paper proposes and implements a GPS-location based SNS data mapping, analysis, and visualization system, called Smart SNS Map, which collects SNS data from Twitter and Instagram using hundreds of PlanetLab nodes distributed across the globe. Like no other previous systems, our system uniquely supports a variety of functions, including GPS-location based mapping of collected tweets and Instagram photos, keyword-based tweet or photo searching, real-time heat-map visualization of tweets and instagram photos, sentiment analysis, word cloud visualization, etc. Overall, a system like this, admittedly still in a prototype phase though, is expected to serve a role as a sort of social weather station sooner or later, which will help people understand what are happening around the SNS users, systems, society, and how they feel about them, as well as how they change over time and/or space.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.95-104
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• 2004

This paper proposes an efficient remote video evaluation system that is matched well with personalized characteristics of students using information filtering based on user profile. For making a question in forms of video, a key frame extraction method based on coordinate, size and color information is proposed. And Question-mating intervals are extracted using gray-level histogram difference and time window. Also, question-making method that combined category-based system with keyword-based system is used for efficient evaluation. Therefore, students can enhance their study achievement through both supplementing their inferior area and preserving their interest area.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.91-110
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• 2002

Recently, to overcome the limit of keyword based retrieval system, the study based structured document has been studied. But it is hard for structured retrieval system to adapt a real service, in this paper, we propose a method of retrieval mechanism for the fulltext of XML documents. We explain DTD of XML based report, extracting navigation information and planing to adapt the retrieval system for article retrieval. Using the fulttext retrieval scheme, suggested system can be an alternative plan of professional structured based retrieval system.