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A Study on Fruits Characteristics of the Chosen Dynasty through the Analysis of Chosenwangjoeshirok Big Data (빅데이터 분석을 통한 조선시대 과실류 특성 연구)

  • Kim, Mi-Hye
    • Journal of the Korean Society of Food Culture
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    • v.36 no.2
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    • pp.168-183
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    • 2021
  • Using the big data analysis of the Choseonwangjosilrok, this research aimed to figure out the fruits' types, prevalence, seasonal appearances as well as the royalty's perspective on fruits during Choseon period. Choseonwangjosilrok included nineteen kinds of fruits and five kinds of nuts, totaling 1,601 cases at 72.8% and 533 cases at 24.2% respectively. The text recorded fruits being used as: tributes for kings, gifts from kings to palace officials, tomb offerings, county specialties, trade goods or gifts to the foreign ambassadors, and medicine ingredients in oriental pharmacy. Seasonally the fruits appeared demonstrating an even distribution. Periodic characteristics were observed in decreasing quantity chronologically. From fifteenth century to nineteenth century, the fruits with timely features were seen: 804 times at 36.6%, 578 times at 26.3%, 490 times at 22.3%, 248 times at 11.3%, and 78 times at 3.5% respectively. In fifteenth century: citrons, quinces, pomegranates, cherries, permissions, watermelons, Korean melons, omija, walnuts, chestnuts, and pine nuts appeared most frequently. In sixteenth century: pears, grapes, apricots, peaches, and hazelnuts appeared most frequently. In seventeenth century: tangerines and dates appeared most frequently. In eighteenth century, trifoliate orange was the most frequently mentioned fruit.

A Study on Space Consumption Behavior of Contemporary Consumers -Focusing on Analysis of Social Media Big Data- (현대 소비자의 공간소비행동에 관한 연구 -소셜미디어 데이터 분석을 중심으로-)

  • Ahn, Suh Young;Koh, Ae-Ran
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.5
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    • pp.1019-1035
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    • 2020
  • This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.

The Necessity of Startup Cultures Enhancement in a Competitive Business Environment

  • CHUN, Sung-Gil;LEE, Cheol-Gyu
    • The Journal of Industrial Distribution & Business
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    • v.12 no.9
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    • pp.19-29
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    • 2021
  • Purpose: To thrive a competitive advantage in the highly competitive global market, a company must establish a strong startup culture, which creates a workplace environment that values innovation and creativity in solving business-related problems. This study investigates the importance of enhancing startup culture in a competitive environment to improve organizational performance, production and hence produce higher returns. Research design, data and methodology: We conducted the qualitative content analysis and its steps seek to ensure that the researcher adheres to a systematic analysis of the data. The method is used for subjective examination of content in any text data and the five steps minimize cases of errors or repetition in used content. Results: Our investigation based on previous literature resources indicates that leading strategies and creating a pleasant working environment are vital behaviors that companies should consider adopting and implementing to achieve a beneficial startup culture full of productivity and massive returns. Conclusion: This research aimed to discuss the necessity of startup culture's enhancement for for-profit companies and found that the adoption of a startup culture in a company is critical to its success. It is vital to building a solid startup culture to grow and gain a competitive advantage in the highly competitive business world.

Distribution of Competitiveness and Foreign Direct Investment using Autoregressive Distributed Lag Model

  • PHAM, Huong Thi Thu;PHAM, Nga Thi
    • Journal of Distribution Science
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    • v.20 no.8
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    • pp.1-8
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    • 2022
  • Purpose: Research on attracting foreign direct investment (FDI) plays an important role in helping provinces attract more FDI projects. However, with local competition, FDI enterprises also have to consider their investment. This study evaluates the provincial competitiveness to attract FDI in Thai Nguyen province, a province of Vietnam. In which provincial distribution of competitiveness is measured through nine indicators. Research design, data, and methodology: The study collects data (FDI and the provincial competitiveness index) from 2006 to 2020. The study uses Autoregressive Distributed Lag (ARDL) to text the impact of distribution of competitivenes on foreign direct investment. With time-series, the ARDL is suitable for data analysis. Results: The regression results indicate that the competition index of market entry and informal costs negatively impact attracting FDI into the province; The human resource training quality index has a positive effect on FDI. The results show that FDI enterprises pay much attention to business establishment procedures, hidden costs, and quality of human resources in the province. Conclusions: At the same time, in terms of practice, the results of this study, the authors also offer solutions to help improve the ability to attract FDI into Thai Nguyen province. The significant provincial competitiveness indicators should be taken into account for improvement first.

Research on R&D Planning Through NLP Analysis of Patent Information: Focusing on Display Technology (특허정보의 NLP 분석을 통한 R&D 계획수립 방안 연구: 디스플레이 기술 분석을 중심으로)

  • Kim, Jung-Heui;Kim, Young-Min
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.5
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    • pp.817-826
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    • 2022
  • Patent information describes the history of technological progress in the relevant field, so it can be usefully used to identify trends in technological development and change and to establish R&D development strategies. This study proposes a method to identify the needs and problems of technology development at the planning stage of the R&D process and to analyze core technologies through patent analysis using Natural Language Processing(NLP) technology. As a big data source, collected patent documents registered in Google Patents for foldable technology, the latest technology in the display industry, and then extracted keywords using NLP analyzer. By classifying the extracted keywords into needs and problems for technology development, developed technology and materials, identified the needs of the market and customers and analyzed the technologies being researched and developed. Unlike previous studies that performed patent analysis, this methodology is different in that it can quickly and conveniently analyze the latest technology trends from big data called patents even if you do not have specialized knowledge and skills in the text mining. This study contributes to the digitalization of the R&D process based on data analysis.

A Study on the Awareness of Artificial Intelligence Development Ethics based on Social Big Data (소셜 빅데이터 기반 인공지능 개발윤리 인식 분석)

  • Kim, Marie;Park, Seoha;Roh, Seungkook
    • Journal of Engineering Education Research
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    • v.25 no.3
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    • pp.35-44
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    • 2022
  • Artificial intelligence is a core technology in the era of digital transformation, and as the technology level is advanced and used in various industries, its influence is growing in various fields, including social, ethical and legal issues. Therefore, it is time to raise social awareness on ethics of artificial intelligence as a prevention measure as well as improvement of laws and institutional systems related to artificial intelligence development. In this study, we analyzed unstructured data, typically text, such as online news articles and comments to confirm the degree of social awareness on ethics of artificial intelligence development. The analysis showed that the public intended to concentrate on specific issues such as "Human," "Robot," and "President" in 2018 to 2019, while the public has been interested in the use of personal information and gender conflics in 2020 to 2021.

Seasonal Weather Factors and Sensibility Change Relationship via Textmining

  • Yeo, Hyun-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.8
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    • pp.219-224
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    • 2022
  • The Korea Meteorological Administration(KMA) has been released life-related indexes such as 'Life industrial weather information' and 'Safety weather information' while other countries' meteorological administrations have been made 'Human-biometeorology' and 'Health meteorology' indexes that concern human sensibility effections to diverse criteria. Although human sensibility changes have been studied in psychological research criteria with diverse and innumerous application areas, there are not enough studies that make data mining based validation of sensibility change factors. In this research I made models to estimate sensibility change caused by weather factors such as temperature and humidity, and validated by collecting sensibility data from SNS text crawling and weather data from KMA public dataset. By Logistic Regression, I clarify factors affecting sensibility changes.

Multimedia Document Databases : Representation, Query Processing and Navigation

  • Kalakota, Ravi S.;Whinston, Andrew B.
    • The Journal of Information Technology and Database
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    • v.1 no.1
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    • pp.31-62
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    • 1994
  • Information systems for application areas like office automation, customer service or computer aided manufacturing are usually highly interactive and deal with complex document structures composed of multiple media formats. For the realization of these systems, nonstandard database systems, which we call document databases, need to handle different types of coarse-and fine-grained document objects(like full-text documents, graphics and images), hierarchical and non-hierarchical relationships between objects(like composition-links and cross-references using hypertext structures) and document attributes of different types such as formatting/presentation information and access control. In this paper, we present the underlying data model for document databases based on descriptive markup languages that provide mechanisms for specifying the logical structure(or schema) of individual documents stored in the database. We then describe extensions to the data model for supporting notion of composite structures("join" operators for documents) --composition and hyperlinking mechanisms for representing compound documents and inter-linked documents as unique entites separate from their components. Furthermore, due to the interactive nature of the application domains, the database system in conjunction with clients(or browsers) has to support visual navigation and graphical query mechanisms. We describe the functionality of a new user interface paradigm called HyBrow for meeting the above mentioned requirements. The underlying implementation strategy is also discussed.discussed.

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Qualitative Study: The Development of Music Business Distribution Channels to Attract Potential Customers

  • Jeong-Eun PARK
    • Journal of Distribution Science
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    • v.21 no.6
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    • pp.13-20
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    • 2023
  • Purpose: This research explores the development of music business distribution channels to attract potential customers based on the current and prior literature. As a result, the research will provide solutions for practitioners in the music distribution channel how they create effective channel in new industry phase which has experienced significant changes due to technological advancement and consumer behavior. Research design, data, and methodology: To obtain textual data in the literature storage, the author conducted content analysis. Even though there are numerous textual resources, selecting only high-quality text data that is only peer-reviewed journal articles and books consistently indicate a high degree of reliability and validity to keep the advantage form content analysis approach. Results: The present study figured out that there are five strategies to attract potential consumers in the music distribution channel, such as (1) 'Marketing Mix', (2) 'Streaming Platforms and Online Music Stores', (3) 'Brick and Mortar Stores and Concerts, and Events', (4) 'Platforms Exclusives and Limited-Edition Merchandise', and 'Partnerships and collaborations. Conclusions: In sum, the practitioners need to consider include building relationships with the fans, studying and understanding their target market, utilizing multiple available distribution channels, embracing new technologies, and analyzing the effectiveness of the adopted distribution channels.

A Study on the Perception of Metaverse Fashion Using Big Data Analysis

  • Hosun Lim
    • Fashion & Textile Research Journal
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    • v.25 no.1
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    • pp.72-81
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    • 2023
  • As changes in social and economic paradigms are accelerating, and non-contact has become the new normal due to the COVID-19 pandemic, metaverse services that build societies in online activities and virtual reality are spreading rapidly. This study analyzes the perception and trend of metaverse fashion using big data. TEXTOM was used to extract metaverse and fashion-related words from Naver and Google and analyze their frequency and importance. Additionally, structural equivalence analysis based on the derived main words was conducted to identify the perception and trend of metaverse fashion. The following results were obtained: First, term frequency(TF) analysis revealed the most frequently appearing words were "metaverse," "fashion," "virtual," "brand," "platform," "digital," "world," "Zepeto," "company," and "game." After analyzing TF-inverse document frequency(TF-IDF), "virtual" was the most important, followed by "brand," "platform," "Zepeto," "digital," "world," "industry," "game," "fashion show," and "industry." "Metaverse" and "fashion" were found to have a high TF but low TF-IDF. Further, words such as "virtual," "brand," "platform," "Zepeto," and "digital" had a higher TF-IDF ranking than TF, indicating that they had high importance in the text. Second, convergence of iterated correlations analysis using UNICET revealed four clusters, classified as "virtual world," "metaverse distribution platform," "fashion contents technology investment," and "metaverse fashion week." Fashion brands are hosting virtual fashion shows and stores on metaverse platforms where the virtual and real worlds coexist, and investment in developing metaverse-related technologies is under way.