• 전자통신동향분석
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• 제38권5호
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• pp.51-60
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• 2023

Quantum machine learning (QML) is an area of quantum computing that leverages its principles to develop machine learning algorithms and techniques. QML is aimed at combining traditional machine learning with the capabilities of quantum computing to devise approaches for problem solving and (big) data processing. Nevertheless, QML is in its early stage of the research and development. Thus, more theoretical studies are needed to understand whether a significant quantum speedup can be achieved compared with classical machine learning. If this is the case, the underlying physical principles may be explained. First, fundamental concepts and elements of QML should be established. We describe the inception and development of QML, highlighting essential quantum computing algorithms that are integral to QML. The advent of the noisy intermediate-scale quantum era and Google's demonstration of quantum supremacy are then addressed. Finally, we briefly discuss research prospects for QML.

• 전자통신동향분석
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• 제38권2호
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• pp.56-65
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• 2023

The combination between metaverse and non-fungible token (NFT), which opens up new opportunities for the media industry, raised expectations for a new economic system and business model. Of course, last year, various institutions and researchers continuously introduce representative metaverse services and business strategies such as Roblox, Fortnite, and ZEPETO. However, as 2022 progresses, the reaction to the metaverse is tepid than expected. Search volume on Google has been continuously decreasing. Furthermore, skepticism, regarded as one of the special phenomena caused by the coronavirus disease 2019 pandemic, is expanding since December 2021. Nevertheless, analysis or contemplation of a new business model related to the metaverse, which is still ongoing, is essential for those who must prepare for the future. The reason is that even if without being activated now, advanced preparation can help when various problems arise. In this study, we look at the metaverse and NFT biz models and estimate a picture of the future. In other words, the social and economic problems that may arise when the business model is expanded are summarized, and technical and policy measures are derived as solutions.

• Journal of Forest and Environmental Science
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• 제34권1호
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• pp.46-49
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• 2018

This study aims to explore the knowledge structure of the leopard cat (Prionailurus bengalensis) research during the period of 1952-2017. Data was collected from Google Scholar and Research Information Service System (RISS), and a total of 482 author keywords from 125 papers from peer-reviewed scholarly journals were retrieved. Co-word analysis was applied to examine patterns and trends in the leopard cat research by measuring the association strengths of the author keywords along with the descriptive analysis of the keywords. The result shows that the most commonly used keywords in leopard cat research were Felidae, Iriomte cat, and camera trap except for its English and scientific name, and camera traps became a frequent keyword since 2005. Co-word analysis also reveals that leopard cat research has been actively conducted in Southeast Asia in conjugation with studying other carnivores using the camera traps. Through the understanding of the patterns and trends, the finding of this study could provide an opportunity for the exploration of neglected areas in the leopard cat research and conservation.

• 산경연구논집
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• 제14권9호
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• pp.1-11
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• 2023

Purpose: The cosmetics industry is dynamic and constantly evolving. The hair and beauty field is characterized by being very sensitive to social trends. Therefore, it is necessary to understand the intellectual structure of the social function of hair beauty and to analyze the research and industrial trends related to the beauty field. This study is a literature review and presents specific and practical development plans and growth strategies for the hair care market. Research design, data, and methodology: This review study was conducted by searching PubMed, Google Scholar, Riss, Scopus, and Research Gate. We prepared this by referring to keywords such as the beauty care industry, sustainable development, hair care, hair cosmetics, and hair care market. A total of 468 papers were searched, of which 60 were finally included in this study on the PRISMA flowchart. Results: For good consumption and continuous development of hair cosmetics, it will be necessary to clearly understand the beauty and cosmetic needs of various generations. Conclusions: As income level improvement and quality of life become more important, Korea's beauty industry is attracting a lot of attention as a growth industry that transcends gender and age amid social and cultural development, and its importance is expected to grow in the future.

• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.332-341
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• 2023

Notable trends in the restaurant start-up market after the lifting of social distancing include increasing interest in start-ups, emphasizing the importance of food quality and diversity, decreasing the relative importance of delivery services, and increasing interest in certain industries. The data collection period is three years from April 2021 to May 2023, including before and after social distancing, and texts extracted from blogs, news, cafes, web documents, and intellectuals provided by Naver, Daum, and Google were collected. For the collected data, the top 30 words were derived through a refining process. In addition, based on April 2021, the application period of social distancing, data from April 2021 to April 2022, and data from May 2022 to May 2023, Through these changes in trends, founders can capture new opportunities in the market and develop start-up strategies. In conclusion, this paper provides important insights for founders in accurately understanding the changes in food service start-up trends and in developing strategies appropriate to the current market situation.

• 한국통신학회논문지
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• 제37B권11호
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• pp.1058-1071
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• 2012

본 연구는 생태계 중심으로 변화하는 ICT 산업 환경 하에서 국내 ICT 기업들이 생태계 경쟁력을 갖기 위해 필요한 정책을 제안한다. 이를 위해 본 연구에서는 ICT 사용자들의 특성 및 소비 트렌드 변화를 분석하고, 비즈니스 생태계 이론을 바탕으로 글로벌 ICT 기업인 애플과 구글의 생태계 추진 전략을 살펴보았다. 또한, 국내 ICT 산업의 문제점을 살펴보고 해외 ICT 정책을 분석하여 국내 기업들이 생태계 경쟁력을 강화하기 위해 필요한 정책 방향을 스마트한 생태계 조성, 전략적인 생태계 육성, 그리고 지속가능한 생태계의 3단계로 구분하여 제안하였다. 본 연구의 결과는 ICT 생태계 조성을 지원하기 위한 정부 정책 수립에 유용한 지침과 시사점을 제공할 것이다.

• The Journal of Asian Finance, Economics and Business
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• 제5권4호
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• pp.45-56
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• 2018

The paper aims to examine relationships between search-based sentiment and stock market reactions in Vietnam. This study constructs an internet search-based measure of sentiment and examines its relationship with Vietnamese stock market returns. The sentiment index is derived from Google Trends' Search Volume Index of financial and economic terms that Vietnamese searched from January 2011 to June 2018. Consistent with prediction from sentiment theories, the study documents significant short-term reversals across three major stock indices. The difference from previous literature is that Vietnam stock market absorbs the contemporaneous decline slower while the subsequent rebound happens within a day. The results of the study suggest that the sentiment-induced effect is mainly driven by pessimism. On the other hand, optimistic investors seem to delay in taking their investment action until the market corrects. The study proposes a unified explanation for our findings based on the overreaction hypothesis of the bearish group and the strategic delay of the optimistic group. The findings of the study contribute to the behavioral finance strand that studies the role of sentiment in emerging financial markets, where noise traders and limits to arbitrage are more obvious. They also encourage the continuous application of search data to explore other investor behaviors in securities markets.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• 지능정보연구
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• 제28권3호
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• pp.1-22
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• 2022

본 연구는 패널 벡터자기회귀 모형을 활용하여 국내 TV 드라마에 대한 디지털 불법복제, 시청률, 온라인 입소문 간의 동태적 관계를 종합적으로 분석하였다. 주요 분석결과는 다음과 같다. 첫째, 시청률은 디지털 불법복제에 부정적 영향을 받지만 구글 버즈에는 긍정적 영향을 받는다. 둘째, 디지털 불법복제는 시청률과 소셜 버즈에 부정적인 영향을 받는다. 셋째, 소셜 버즈와 구글 버즈는 서로 긍정적 영향을 받는다. 영화나 음악에 대한 불법복제 효과 연구는 많이 이루어졌으나 TV 드라마에 대한 연구는 상대적으로 제한적이다. 본 연구는 TV 드라마의 디지털 불법복제 영향을 실증 분석하였으며, 특히 디지털 불법복제가 시청률에 미치는 직접효과 뿐만 아니라 온라인 입소문을 통한 간접효과가 존재함을 실증적으로 밝혔다는 점에서 의의가 있다. 또한 온라인 입소문을 소셜 버즈와 구글 트렌드 지표로 다양화하여 그 효과를 검증함으로써 중요한 실무적 시사점을 제공한다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권9호
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• pp.387-398
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• 2023

코로나 19 유행은 인류 생활 방식과 패턴에 큰 영향을 주었다. 코로나 19는 침 방울(비말)은 물론 공기를 통해서도 감염되기 때문에 가능한 대면 접촉을 피하고 많은 사람이 가까이 모이는 장소는 피할 것을 권고하고 있다. 코로나 19 환자와 접촉했거나 코로나 19 환자가 발생한 장소에 있었던 사람이 코로나 19에 감염되었을 것을 염려한다면 구글에서 코로나 19 증상을 찾아볼 것이라고 충분히 예상해 볼 수 있다. 본 연구에서는 과거 독감 감시와 관리에 중요 역할을 했었던 구글 트렌드(Google Trends)를 다시 소환하고 코로나 19 확진자수 데이터와 결합하여 미래의 코로나 19 확진자수를 예측할 수 있을지 딥러닝 모델(DNN & LSTM)을 사용한 탐색적 데이터 분석을 실시하였다. 특히 이 연구에 사용된 검색어 빈도 데이터는 공개적으로 사용할 수 있으며 사생활 침해의 우려도 없다. 심층 신경망 모델(DNN model)이 적용되었을 때 한국에서 가장 많은 인구가 사는 서울(960만 명)과 두 번째로 인구가 많은 부산(340만 명)에서는 검색어 빈도 데이터를 포함하여 예측했을 때 더 낮은 오류율을 기록했다. 이와 같은 분석 결과는 검색어 빈도 데이터가 일정 규모 이상의 인구수를 가진 도시에서 중요한 역할을 할 수 있다는 것을 보여주는 것이다. 우리는 이와 같은 예측이 더 강력한 예방 조치의 실행이나 해제 같은 정책을 결정하는데 근거 자료로 충분히 사용될 수 있을 것으로 믿는다.