A Method of Predicting News Update Time Combining Exponential Smoothing and Naive Bayes

摘要

The time of web page update appears to be erratic, how the user can fast access to valuable information has become one of the hot spots. From the view of application, we can use mathematical models to forecast the update time of news reports, although it can not be completely accurate. In this paper, we proposed a combined predict algorithm for news update. Firstly, we applied the Exponential Smoothing method to our dataset. Secondly, we leveraged the Naive Bayes Model for prediction. Finally, we combined two methods for Combination Forecasting. Through the experiments, we show that Combination Forecasting method outperforms other methods while estimating localized rate of updates.