• Title/Summary/Keyword: People Analytics

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A Study on Activation Method of Website through Log Analysis -Focused on the website(MMWS) for research the Mediterranean Area- (로그 분석을 통한 웹사이트 활성화 방안에 대한 연구 - 지중해지역 연구를 위한 웹사이트(MMWS)를 중심으로 -)

  • Kang, Ji-Hoon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.907-916
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    • 2017
  • Recently, various studies related to ICT convergence have been made. Recently, various studies related to ICT convergence have been made. In the academic field, the demand for ICT convergence is on the rise. For example, Digital Humanities and Area Informatics are representative. Area Studies means to study the culture of a specific area in an integrated way. In this regard, researchers who specialize in researching overseas area generally use websites to obtain information related to the area. The Multilingual Mediterranean Web Service System(MMWS), which is operated by the Institute for Mediterranean Studies of Busan University of Foreign Studies is a web site that provides professional and general information to researchers or ordinary people studying in the Mediterranean area among overseas area. In this paper, we analyzeoverseas web sites the MMWS and discuss how to activate web sites based on the analysis results. In details, it analyze MMWS through log analysis and use Google Analytics, a log analysis system provided by Google for analysis. Also study how to use ICT convergence contents as a website activation method.

A Study on analyzing brand character of myth material, relevant keyword and relevance with big data of portal site and SNS (포털사이트, SNS의 빅데이터를 이용한 신화소재의 브랜드 캐릭터와 연관어, 연관도 분석)

  • Oh, Sejong;Doo, Illchul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.11 no.1
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    • pp.157-169
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    • 2015
  • In digital marketing, means of public relations and marketing of enterprises are changing into marketing techniques of predictive analytics. A significant study can be carried out by an analysis of 'the patterns of customers' uses' using big data on major portal sites and SNSs and their correlation with related keywords. This study analyzes the origins of mythological characters in major brands such as Nike, Hermes, Versace, Canon and Starbucks. Also, it extracts related keywords and relevance using big data on portal sites and SNS and their correlation. Nike marketing that reminds people of 'the goddess of victory, Nike' formed a good combination of the brand with relevance. Most of them are based on Greek mythology and have rich materials for storytelling and artistic values in common. Hopefully, this case analysis of foreign brands would become a starting point of discovering the materials of the domestic mythological characters.

The Big Data Analytics Regarding the Cadastral Resurvey News Articles

  • Joo, Yong-Jin;Kim, Duck-Ho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.6
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    • pp.651-659
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    • 2014
  • With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.

A Study on the Analysis of Necessary Information to Explore the Employees' Teamwork Behavior (직원의 팀워크 행동 예측을 위한 필요 정보 분석에 관한 연구)

  • Youngshin Kim
    • Journal of Internet Computing and Services
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    • v.25 no.3
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    • pp.83-92
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    • 2024
  • Recently, the importance of HR analytics for data-based decision-making in establishing and operating an effective human resource management system for companies is increasing. In addition, there is growing interest in the effect of employees' perceptions of organizational justice on positive organizational behavior. Therefore, in this study, among the various factors affecting teamwork behavior, we analyzed the impact on teamwork behavior such as perception of organizational justice and organizational culture. Organizational justice has a significant impact on the formation of members' attitudes, but its meaning may vary depending on the organizational context. In this study, we divided organizational justice into four types (procedural, distributive, interpersonal, and informational fairness) and confirmed their impact on teamwork behavior. In addition, organizational culture was divided into hierarchy culture and innovation culture, and how to regulate these relationships was examined. To analyze these relationships, individual-level data collected from 657 people at domestic companies were used for analysis. According to the analysis results, in a hierarchical culture, procedural justice and information justice had a positive influence on teamwork behavior through the mediating process of job satisfaction, and in an innovative culture, interpersonal justice and information justice had a positive influence on teamwork behavior through job satisfaction. It was confirmed to have a (+) effect. These research results provide implications for people management by indicating that, although organizational justice is important to members and organizations, it may be perceived differently and have different meanings depending on the organizational context. Through the use of the information presented in this study, we will provide value that can effectively and efficiently implement a company's human resource management system.

Towards Sustainable Environmental Policy and Management in the Fourth Industrial Revolution: Evidence from Big Data Analytics

  • CHOI, Choongik;KIM, Chunil;KIM, Chulmin
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.3
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    • pp.185-192
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    • 2019
  • This study is to explore the relationship between the Fourth Industrial Revolution and the environment using the big data methodology. We scrutinize the trend of the Fourth Industrial revolution, in association with the environment, and provide implications for a more desirable future environmental policy. The results show that the Industrial Revolution has been generally perceived as negative to environment before the 2010s, while it has been widely regarded as positive after the period. It is highly expected that the Fourth Industrial Revolution will be capable of functioning as a new alternative to enhance the quality of the biophysical and social environment. This study justifies that the new wave of technological development may serve as a cure for the enhancement of the environmental quality. The positive linkage between the new technological development and the environment from this study clearly indicates that the environmental industry and environmental technologies will be key economic factors in the next-generation society. They should be of critical importance in shaping our cities into clearer and greener spaces, and people will continuously depend on the development of new environmental technologies in order to correct environmental damages.

Business Innovation Through Spatial Data Analysis: A Multi-Case Analysis (공간 데이터 분석 기반의 비즈니스의 혁신: 해외 사례 분석을 중심으로)

  • Ham, YuKun
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.83-97
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    • 2019
  • With sensor and communication technology development, spatial data related to business activities is exploding. Spatial data is now evolving into atypical data about space over three dimensions, away from two-dimensional geographic data. In addition to the Fourth Industrial Revolution, which connects the virtual space with the real space, there is a great opportunity for companies to utilize it. The analysis of recent overseas cases shows that it is possible to analyze customized services by understanding the situation of customers and objects located in the space, to manage risk, and furthermore to innovate business processes by analyzing spatial data. In the future, business innovation that combines spatial data from various sources and real-time analysis of relationships and situations between people and objects in space is expected to expand in all business fields.

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New Trends and Challenges of Internet Marketing

  • Nosshi, Anthony;Saad, Aziza;Senousy, M. Badr
    • Asia pacific journal of information systems
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    • v.25 no.2
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    • pp.337-355
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    • 2015
  • The Internet has become one of the most important channels for people to communicate and for companies to implement their sales promotion activities, such as advertising. Marketing and advertising attempt to influence customers' attitude to persuade them to choose to buy the advertisers' products instead of the competitors'. With the different forms of online marketing, such as search engine marketing, email marketing, and mobile marketing, advertisers can find more effective strategies to attract the attention of more targeted audiences. With the emergence of the social web (web 2.0), a new platform was introduced called social networks. This paper presents the current work in internet marketing activities until web 2.0, and conducts a social network analysis to aid in data extraction. Marketing and advertising companies have understood the power of information for a very long time. The more knowledge these companies have on the demographics, consumer habits, and preferences of particular customer types, the more they can tailor their product offerings, and the more sales they can make. This paper aims to understand the internet marketing concepts as well as present challenges and work directions in internet marketing.

A Study on Big Data Analytics Services and Standardization for Smart Manufacturing Innovation

  • Kim, Cheolrim;Kim, Seungcheon
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.91-100
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    • 2022
  • Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

Food Security through Smart Agriculture and the Internet of Things

  • Alotaibi, Sara Jeza
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.33-42
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    • 2022
  • One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

Trends in Development of Intelligent Response Technology for 112 and 119 Emergency Calls (112, 119 긴급신고 대응 지능화 기술 개발 동향)

  • M.J. Lee;H.H. Park;M.S. Baek;E.J. Kwon;S.W. Byon;Y.S. Park;E.S. Jung;H.S. Park
    • Electronics and Telecommunications Trends
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    • v.38 no.3
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    • pp.57-65
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    • 2023
  • Emergency numbers, such as 112 and 119, are used in many countries to connect people in need with emergency services such as police, fire, and medical assistance. We describe development directions of intelligent response technology for emergency calls. The development of this technology refers to enhancing the efficiency and effectiveness of response systems by using advanced methods such as artificial intelligence, machine learning, and big data analytics. We focus on a system that assists the receptionist of an emergency call. In the future, the recognition rate and decision-making accuracy of intelligent response technologies should be improved considering characteristics of public safety and emergency domain data. Although the current technology remains at the level of assisting a receptionist, a fully autonomous response technology is expected to emerge in the future.