• Title/Summary/Keyword: Keyword Data

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A Study on Establishing a Market Entry Strategy for the Satellite Industry Using Future Signal Detection Techniques (미래신호 탐지 기법을 활용한 위성산업 시장의 진입 전략 수립 연구)

  • Sehyoung Kim;Jaehyeong Park;Hansol Lee;Juyoung Kang
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.249-265
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    • 2023
  • Recently, the satellite industry has been paying attention to the private-led 'New Space' paradigm, which is a departure from the traditional government-led industry. The space industry, which is considered to be the next food industry, is still receiving relatively little attention in Korea compared to the global market. Therefore, the purpose of this study is to explore future signals that can help determine the market entry strategies of private companies in the domestic satellite industry. To this end, this study utilizes the theoretical background of future signal theory and the Keyword Portfolio Map method to analyze keyword potential in patent document data based on keyword growth rate and keyword occurrence frequency. In addition, news data was collected to categorize future signals into first symptom and early information, respectively. This is utilized as an interpretive indicator of how the keywords reveal their actual potential outside of patent documents. This study describes the process of data collection and analysis to explore future signals and traces the evolution of each keyword in the collected documents from a weak signal to a strong signal by specifically visualizing how it can be used through the visualization of keyword maps. The process of this research can contribute to the methodological contribution and expansion of the scope of existing research on future signals, and the results can contribute to the establishment of new industry planning and research directions in the satellite industry.

A design and implementation of the management system for number of keyword searching results using Google searching engine (구글 검색엔진을 활용한 키워드 검색결과 수 관리 시스템 설계 및 구현)

  • Lee, Ju-Yeon;Lee, Jung-Hwa;Park, Yoo-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.5
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    • pp.880-886
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    • 2016
  • With lots of information occurring on the Internet, the search engine plays a role in gathering the scattered information on the Internet. Some search engines show not only search result pages including search keyword but also search result numbers of the keyword. The number of keyword searching result provided by the Google search engine can be utilized to identify overall trends for this search word on the internet. This paper is aimed designing and realizing the system which can efficiently manage the number of searching result provided by Google search engine. This paper proposed system operates by Web, and consist of search agent, storage node, and search node, manage keyword and search result, numbers, and executing search. The proposed system make the results such as search keywords, the number of searching, NGD(Normalized Google Distance) that is the distance between two keywords in Google area.

Unstructured Data Processing Using Keyword-Based Topic-Oriented Analysis (키워드 기반 주제중심 분석을 이용한 비정형데이터 처리)

  • Ko, Myung-Sook
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.521-526
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    • 2017
  • Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

A Study on MIS Curriculum and NCS-based Big Data Analysis Job Competency Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 MIS 교과정보와 NCS 기반 빅데이터 분석 직무역량에 대한 연구)

  • Lee, Taewon;Sung, Haengnam;Kim, Eun-Jung
    • The Journal of Information Systems
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    • v.29 no.4
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    • pp.101-121
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    • 2020
  • Purpose The purpose of this study is to understand the current status of MIS curriculum and to find ways to improve it. In addition, the results of the research can be used as basic data for improving MIS curriculum. Design/methodology/approach A research framework was designed to derive research results using the keyword network analysis method of this study: 1) Keywords were extracted based on the six units of the big data analysis job competency. 2) And based on the extracted keywords, the relationship between the keywords and MIS curriculum for each university was identified. Findings In the MIS curriculum information of a few universities, education related to big data analysis was conducted. 1) In the MIS curriculum of a few universities, education related to big data analysis was conducted. However, MIS curriculum of the university, which is the subject of analysis, education focused on concepts and theory rather than practical education was conducted. 2) And it was confirmed that there is a difference from the education required by the industry.

A Study on the User Experience at Unmanned Cafe Using Big Data Analsis: Focus on text mining and semantic network analysis (빅데이터를 활용한 무인카페 소비자 인식에 관한 연구: 텍스트 마이닝과 의미연결망 분석을 중심으로)

  • Seung-Yeop Lee;Byeong-Hyeon Park;Jang-Hyeon Nam
    • Asia-Pacific Journal of Business
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    • v.14 no.3
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    • pp.241-250
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    • 2023
  • Purpose - The purpose of this study was to investigate the perception of 'unmanned cafes' on the network through big data analysis, and to identify the latest trends in rapidly changing consumer perception. Based on this, I would like to suggest that it can be used as basic data for the revitalization of unmanned cafes and differentiated marketing strategies. Design/methodology/approach - This study collected documents containing unmanned cafe keywords for about three years, and the data collected using text mining techniques were analyzed using methods such as keyword frequency analysis, centrality analysis, and keyword network analysis. Findings - First, the top 10 words with a high frequency of appearance were identified in the order of unmanned cafes, unmanned cafes, start-up, operation, coffee, time, coffee machine, franchise, and robot cafes. Second, visualization of the semantic network confirmed that the key keyword "unmanned cafe" was at the center of the keyword cluster. Research implications or Originality - Using big data to collect and analyze keywords with high web visibility, we tried to identify new issues or trends in unmanned cafe recognition, which consists of keywords related to start-ups, mainly deals with topics related to start-ups when unmanned cafes are mentioned on the network.

Tendency and Network Analysis of Diet Using Big Data (빅데이터를 활용한 다이어트 현황 및 네트워크 분석)

  • Jung, Eun-Jin;Chang, Un-Jae
    • Journal of the Korean Dietetic Association
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    • v.22 no.4
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    • pp.310-319
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    • 2016
  • Limitation of a questionnaire survey which is widely used is time and money, limited numbers of participants, biased confidence interval and unreliable results. To overcome these, we performed tendency and network analysis of diet using big Data in Koreans. The keyword on diet were collected from the portal site Naver from January 1, 2015 until December 31, 2015 and collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis and seasonality analysis. The results showed that diet menu appeared most frequently by N-gram analysis, even though exercise had the highest frequency by simple frequency analysis. In addition, keyword network analysis were categorized into four groups: diet group, exercise group, commercial diet program company group and commercial diet food group. The analysis of seasonality showed that subjects' interests in diet had increased steadily since February, 2015, although subjects were most interested indiet in July, these results suggest that the best strategies for weight loss are based on diet menu and starting diet before July. As people are especially sensitive to diet trends, researches are needed about annual analysis of big data.

Reactive Routing Keyword based Routing Procedure in MANET (MANET에서의 Reactive Routing Keyword 기반 라우팅 프로시듀어)

  • Park Soo-Hyun;Shin Soo-Young
    • Journal of the Korea Society for Simulation
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    • v.13 no.4
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    • pp.55-69
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    • 2004
  • In MANET(Mobile Ad-hoc Network), unlike in wired networks, a path configuration should be in advance of data transmission along a routing path. Frequent movement of mobile nodes, however, makes it difficult to maintain the configured path and requires re-configuration of the path very often. It may also leads to serious problems such as deterioration of QoS in mobile ad-hoc networks. In this paper, we proposed a Reactive Routing Keyword (RRK) routing procedure to solve those problems. Firstly, we noticed it is possible in RRK routing to assign multiple routing paths to the destination node. We applied this feature into active networks and SNMP information based routing by storing unique keywords in cache of mobile nodes corresponding to present and candidate routings in a path configuration procedure. It was shown that the deterioration of QoS which may observed in Dynamic Source Routing(DSR) protocol was greatly mitigated by using the proposed routing technique.

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A Study on the Multiple Keyword Retrieval Method under the Object-Oriented Multimedia Database Model (객체 지향 멀티미디어 데이터베이스 모델하에서의 다중 키워드 검색 기법에 관한 연구)

  • 석상기;김경창;김기용
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.8
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    • pp.1176-1189
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    • 1993
  • This paper presents the Multiple Keyword Retrieval Method under the Object-Oriented Multimedia Database Model. The multiple keyword registration and retrieval algorithms are developed to reduce the partial matching problem in multimedia data retrieval. For this, proper storage structures of the lookup tables are designed. And also, in order to maintain the constant retrieval time, media data files are organized with B+ tree structure.

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The Perceptions of the Students about Professionalism on the Elementary Teachers' Science Teaching through Network Analysis of Keyword (키워드 네트워크 분석을 통해 알아본 초등교사의 과학수업 전문성에 대한 학생의 인식)

  • Sung, Seung Min;Yeo, Sang-Ihn
    • Journal of Korean Elementary Science Education
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    • v.37 no.1
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    • pp.27-38
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    • 2018
  • The purpose of this study was to investigate the perceptions of the students about professionalism on the elementary teachers' science teaching through network analysis of keyword. For this study, questionnaires were conducted to elementary school students. The collected data were translated by coding and data cleaning. And then analyzed by Gephi 0.9.2 program as a tool of the network analysis. The results of this study were as follows: Top 5 words in betweenness centrality were 'smart, experiment, fun, various, and student understanding'. There was some difference of perceptions of students according to personal backgrounds(gender, grade and interest toward science class). Based on the result of this study, implications to improve elementary teachers' science teaching professionalism were suggested.

Analyzing Knowledge Structure of Defense Area using Keyword Network Analysis

  • Lee, Yong-Kyu;Yoon, Soung-Woong;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.10
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    • pp.173-180
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    • 2018
  • In this paper, we analyzed key keywords and research themes in the field of defense research using keyword network analysis and tried to grasp the whole knowledge structure. To do this, we extracted data from 2,165 research data from defense related research institutes from 2010 to 2017 and applied the Pareto rule to the number of abstracts of words and the number of links between words, We extracted a total of 2,303 words based on the criterion and extracted 204 final key words through component analysis. By analyzing the centrality and cohesiveness through these key words, we confirmed the concept of core research in the defense field and derived a total of 7 large groups and 16 small groups of each group in the knowledge structure of the defense area.