Predicting changes of realtime search words using time series analysis and artificial neural networks

시계열분석과 인공신경망을 이용한 실시간검색어 변화 예측

  • 정민영 (광주여자대학교 실버케어학과)
  • Received : 2017.11.02
  • Accepted : 2017.12.20
  • Published : 2017.12.28


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.


Supported by : 광주여자대학교


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