• Title/Summary/Keyword: 정책 모델링

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A Study on the Research Trends for Smart City using Topic Modeling (토픽 모델링을 활용한 스마트시티 연구동향 분석)

  • Park, Keon Chul;Lee, Chi Hyung
    • Journal of Internet Computing and Services
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    • v.20 no.3
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    • pp.119-128
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    • 2019
  • This study aims to analyze the research trends on Smart City and to present implications to policy maker, industry professional, and researcher. Cities around globe have undergone the rapid progress in urbanization and the consequent dramatic increase in urban dwellings over the past few decades, and faced many urban problems in such areas as transportation, environment and housing. Cities around the globe are in a hurry to introduce Smart City to pursue a common goal of solving these urban problems and improving the quality of their lives. However, various conceptual approaches to smart city are causing uncertainty in setting policy goals and establishing direction for implementation. The study collected 11,527 papers titled "Smart City(cities)" from the Scopus DB and Springer DB, and then analyze research status, topic, trends based on abstracts and publication date(year) information using the LDA based Topic Modeling approaches. Research topics are classified into three categories(Services, Technologies, and User Perspective) and eight regarding topics. Out of eight topics, citizen-driven innovation is the most frequently referred. Additional topic network analysis reveals that data and privacy/security are the most prevailing topics affecting others. This study is expected to helps understand the trends of Smart City researches and predict the future researches.

Policy Modeling for Efficient Reinforcement Learning in Adversarial Multi-Agent Environments (적대적 멀티 에이전트 환경에서 효율적인 강화 학습을 위한 정책 모델링)

  • Kwon, Ki-Duk;Kim, In-Cheol
    • Journal of KIISE:Software and Applications
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    • v.35 no.3
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    • pp.179-188
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    • 2008
  • An important issue in multiagent reinforcement learning is how an agent should team its optimal policy through trial-and-error interactions in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for multiagent reinforcement teaming tend to apply single-agent reinforcement learning techniques without any extensions or are based upon some unrealistic assumptions even though they build and use explicit models of other agents. In this paper, basic concepts that constitute the common foundation of multiagent reinforcement learning techniques are first formulated, and then, based on these concepts, previous works are compared in terms of characteristics and limitations. After that, a policy model of the opponent agent and a new multiagent reinforcement learning method using this model are introduced. Unlike previous works, the proposed multiagent reinforcement learning method utilize a policy model instead of the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper. the Cat and Mouse game is introduced as an adversarial multiagent environment. And effectiveness of the proposed multiagent reinforcement learning method is analyzed through experiments using this game as testbed.

An Analysis of the Support Policy for Small Businesses in the Post-Covid-19 Era Using the LDA Topic Model (LDA 토픽 모델을 활용한 포스트 Covid-19 시대의 소상공인 지원정책 분석)

  • Kyung-Do Suh;Jung-il Choi;Pan-Am Choi;Jaerim Jung
    • Journal of Industrial Convergence
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    • v.22 no.6
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    • pp.51-59
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    • 2024
  • The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

A Topic Analysis of Fine Particle Matter by Using Newspaper Articles (신문기사를 이용한 미세먼지 이슈의 토픽 분석)

  • Yang, Ji-Yeon
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.1-14
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    • 2022
  • This study aims to identify topics in newspaper articles related to fine particle matter and to investigate the characteristics and time series trend of each topic. Related national newspaper articles during 1990 and 2021 were collected from Bigkinds. A total of 18 topics have been discovered using LDA, and 11 clusters deduced from clustering. Hot topics include related products/residence, overseas cause(China), power plant as a domestic cause, nationwide emergency reduction measures, international cooperation, political issues, current situation & countermeasure in other countries, and consumption patterns. Cold topics include the concentration standard and indoor air quality improvement. These findings would be useful in inferring the political direction and strategies. In particular, the consumer protection policy should be expanded as the related market is growing. It will also be necessary to pursue policies that will promote public safety and health, and that will enhance public consensus and international cooperation.

News data LDA on North Korean defector entrepreneurship: Focusing on the comparison of government policies from 2013 to 2021 (북한이탈주민 창업에 관한 뉴스 데이터 토픽 모델링 분석: 2013~2021년까지 정부 정책 비교를 중심으로)

  • Mun, Jun-Hwan
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.145-155
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    • 2022
  • North Korean defectors are experiencing economic hardship due to the prolonged COVID-19 outbreak. In order to solve this problem, interest in starting a business is increasing. This study targeted the current and previous government, and discovered major topics through text mining of news data on North Korean defector starting a business to examine the start-up support policies according to the keynote of the present regime. Additionally, key factors for successful start-ups were derived through interviews with North Korean defectors who have done them. As a result of the analysis, it is necessary to focus on women and the youth, and to actively expand specialized entrepreneurship education and financial support for North Korean defectors. In addition, it was confirmed that there is a need for a practical and continuous entrepreneurship education program.

Understanding Public Opinion by Analyzing Twitter Posts Related to Real Estate Policy (부동산 정책 관련 트위터 게시물 분석을 통한 대중 여론 이해)

  • Kim, Kyuli;Oh, Chanhee;Zhu, Yongjun
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.3
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    • pp.47-72
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    • 2022
  • This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.

A Quantitative Assessment Modeling Technique for Survivality Improvement of Ubiquitous Computing System (유비쿼터스 컴퓨팅 시스템의 생존성 개선을 위한 정량적 분석 모델링 기법)

  • Choi, Chang-Yeol;Kim, Sung-Soo
    • The KIPS Transactions:PartC
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    • v.12C no.5 s.101
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    • pp.633-642
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    • 2005
  • Ubiquitous computing system is about networked processors, which is constructed with one or more computers interconnected by the networks. However, traditional security solution lacks a Proactive maintenance technique because of its focusing on developing the qualitative detection and countermeasure after attack. Thus, in this paper, we propose a quantitative assessment modeling technique, by which the general infrastructure can be improved and the attacks on a specific infrastructure be detected and protected. First of all, we develop the definition of survivality and modeling technique for quantitative assessment modeling with the static information on the system random information, and attack-type modeling. in addition, the survivality analysis on TCP-SYN attack and code-Red worm attack is performed for validating the proposed technique.

기업가정신에 대한 연구동향 분석

  • Jang, Seong-Hui
    • 한국벤처창업학회:학술대회논문집
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    • 2022.04a
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    • pp.73-79
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    • 2022
  • 본 연구는 동시출현단어 분석과 토픽모델링을 통해 기업가정신의 연구주제와 연구 동향을 분석하여 기업가정신 연구에 대한 향후 연구방향을 수립하기 위한 정보를 제공하는 것이 목적이다. 이를 위해 Web of Science 데이터베이스에서 "entrepreneurship"을 기본검색어로 설정하고, 2002년부터 2021년까지 발표한 영어 논문으로 제한하여 기업가정신 논문의 데이터를 다운로드하여 데이터를 확보하였다. 본 연구에서는 VOSviewer 프로그램을 이용하여 동시출현단어 분석을 하였고, R 프로그램을 이용하여 토픽모델링 분석을 하였다. 동시출현단어 분석 결과, 기업가정신과 혁신 클러스터, 기업가정신 교육 클러스터, 사회적 기업가정신과 지속가능성 클러스터, 기업성과 클러스터, 그리고 지식 및 기술이전 클러스터 등 5개의 클러스터로 구분되었다. 토픽모델링 분석 결과, 창업환경 및 경제발전, 국제 기업가정신, 다양한 기업가정신, 벤처기업과 자본조달, 정부정책 및 지원, 사회적 기업가정신, 경영관련 이슈, 지역도시계획 및 개발, 기업가정신 교육, 기업가의 혁신과 성과, 기업가정신 연구, 기업가의 창업의도 등 12개의 토픽으로 분석되었다. 본 연구의 결과는 기업가정신 연구에 대한 전반적인 연구동향을 파악할 뿐만 아니라, 기업가정신과 관련된 어떠한 연구 주제들이 다루어져 왔는지에 대해 분석함으로써 기업가정신에 대한 연구의 이해도를 높이고 기업가정신 연구가 가져올 방향성을 제안하는데 활용할 수 있을 것으로 기대된다.

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Social Media Analysis Based on Keyword Related to Educational Policy Using Topic Modeling (토픽모델링을 이용한 교육정책 키워드 기반 소셜미디어 분석)

  • Chung, Jin-myeong;Park, Young-ho;Kim, Woo-ju
    • Journal of Internet Computing and Services
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    • v.19 no.4
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    • pp.53-63
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    • 2018
  • The traditional mass media function of conveying information and forming public opinion has rapidly changed into an environment in which information and opinions are shared through social media with the development of ICT technology, and such social media further strengthens its influence. In other words, it has been confirmed that the influence of the public opinion through the production and sharing of public opinion on political, social and economic changes is increasing, and this change is already in use on the political campaign. In addition, efforts to grasp and reflect the opinions of the public by utilizing social media are being actively carried out not only in the political area but also in the public area. The purpose of this study is to explore the possibility of using social media based public opinion in educational policy. We collected media data, analyzed the main topic and probability of occurrence of each topic, and topic trends. As a result, we were able to catch the main interest of the public(the 'Domestic Computer Education Time' accounted for 43.99%, and 'Prime Project Selection' topics was 36.81% and 'Artificial Intelligence Program' topics was 7.94%). In addition, we could get a suggestion that flexible policies should be established according to the timing of the curriculum and the subject of the policy even if the category of the policy is same.