• Title/Summary/Keyword: LDA Method

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Trend Analysis using Topic Modeling for Simulation Studies (토픽 모델링을 이용한 시뮬레이션 연구 동향 분석)

  • Na, Sang-Tae;Kim, Ja-Hee;Jung, Min-Ho;Ahn, Joo-Eon
    • Journal of the Korea Society for Simulation
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    • v.25 no.3
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    • pp.107-116
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    • 2016
  • The recent diversification in terms of the scope and techniques used for simulations has highlighted the importance of analyzing state of the art trends and applying these for educational and study purposes. While qualitative methods such as literature research or experts' assessments have previously been used, such methods are in fact likely to reflect the subjective viewpoint of experts, and to involve too much time and money for the results obtained. For the purpose of an objective analysis, a quantitative analysis that included the examination of topics found in domestic academic journal articles was conducted in the present study. In this regard, simulation was found to be most actively used domestically in the electrical and electronic fields. In addition, simulation was also found to be employed for the purpose of education and entertainment in the social sciences. The results of this study are expected to help to facilitate the prediction of the direction of the development of not only the Korea Society for Simulation, but also domestic simulation studies. This study also raises the possibility of applying text mining to trend analysis, and proves that it can be a useful method for deriving future key topics and helping experts' decisions regarding quantitative data.

User Experience Analysis and Management Based on Text Mining: A Smart Speaker Case (텍스트 마이닝 기반 사용자 경험 분석 및 관리: 스마트 스피커 사례)

  • Dine Yeon;Gayeon Park;Hee-Woong Kim
    • Information Systems Review
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    • v.22 no.2
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    • pp.77-99
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    • 2020
  • Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.