• Title/Summary/Keyword: Realtime search word

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Predicting changes of realtime search words using time series analysis and artificial neural networks (시계열분석과 인공신경망을 이용한 실시간검색어 변화 예측)

  • Chong, Min-Yeong
    • Journal of Digital Convergence
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    • v.15 no.12
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    • pp.333-340
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    • 2017
  • Since realtime search words are centered on the fact that the search growth rate of an issue is rapidly increasing in a short period of time, it is not possible to express an issue that maintains interest for a certain period of time. In order to overcome these limitations, this paper evaluates the daily and hourly persistence of the realtime words that belong to the top 10 for a certain period of time and extracts the search word that are constantly interested. Then, we present the method of using the time series analysis and the neural network to know how the interest of the upper search word changes, and show the result of forecasting the near future change through the actual example derived through the method. It can be seen that forecasting through time series analysis by date and artificial neural networks learning by time shows good results.

Selecting a key issue through association analysis of realtime search words (실시간 검색어 연관 분석을 통한 핵심 이슈 선정)

  • Chong, Min-Yeong
    • Journal of Digital Convergence
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    • v.13 no.12
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    • pp.161-169
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    • 2015
  • Realtime search words of typical portal sites appear every few seconds in descending order by search frequency in order to show issues increasing rapidly in interest. However, the characteristics of realtime search words reordering within too short a time cause problems that they go over the key issues of the day. This paper proposes a method for deriving a key issue through association analysis of realtime search words. The proposed method first makes scores of realtime search words depending on the ranking and the relative interest, and derives the top 10 search words through descriptive statistics for groups. Then, it extracts association rules depending on 'support' and 'confidence', and chooses the key issue based on the results as a graph visualizing them. The results of experiments show that the key issue through association rules is more meaningful than the first realtime search word.

An Analysis on Internet Information using Real Time Search Words (실시간 검색어 분석을 이용한 인터넷 정보 관심도 분석)

  • Noh, Giseop
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.4
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    • pp.337-341
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    • 2018
  • As the online media continues to evolve and the mobile computing environment has improved dramatically, the distribution of Internet information has rapidly changed from one-sided to consumer-oriented. Therefore, measuring the interest of Internet information has become an important issue for suppliers and consumers. In this paper, we analyze the Internet information interest by analyzing the duration of real - time query by collecting data for one month by implementing real - time search word provided by domestic Internet information provider.