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Forecasting tourist arrivals with machine learning and internet search index
9 references·16 citing·38 second hop
Forecasting tourist arrivals with machine learning and internet search index (2018)Forecasting tourist arrivals with machine…Forecasting Chinese tourist volume with search engine data (2014)Forecasting Chinese tourist v…Predicting the Present with Google Trends (2012)Predicting the Present with G…Forecasting private consumption: survey-based indicators vs. Google trends (2011)Forecasting private consumpti…Google Econometrics and Unemployment Forecasting (2009)Google Econometrics and Unemp…Tourism demand modelling and forecasting—A review of recent research (2007)Tourism demand modelling and …Comparing Predictive Accuracy (2002)Comparing Predictive AccuracyNumerical distribution functions of likelihood ratio tests for cointegration (1999)Numerical distribution functi…Forecasting tourism demand: A review of empirical research (1995)Forecasting tourism demand: A…Comparing Predictive Accuracy (1994)Comparing Predictive AccuracyTourism and Hospitality Forecasting With Big Data: A Systematic Review of the Literature (2024)Tourism and Hospitality Forec…Does internet public participation slow down environmental pollution? (2022)Does internet public particip…Using SARIMA–CNN–LSTM approach to forecast daily tourism demand (2021)Using SARIMA–CNN–LSTM approac…Forecasting crude oil price with a new hybrid approach and multi-source data (2021)Forecasting crude oil price w…Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making (2021)Artificial intelligence for h…A systematic literature review on the use of big data for sustainable tourism (2021)A systematic literature revie…Tourism Demand Forecasting: A Decomposed Deep Learning Approach (2020)Tourism Demand Forecasting: A…Review of tourism forecasting research with internet data (2020)Review of tourism forecasting…Machine Learning in Internet Search Query Selection for Tourism Forecasting (2020)Machine Learning in Internet …Improving Tourist Arrival Prediction: A Big Data and Artificial Neural Network Approach (2020)Improving Tourist Arrival Pre…Forecasting tourism demand with multisource big data (2020)Forecasting tourism demand wi…Forecasting Tourism Demand with an Improved Mixed Data Sampling Model (2020)Forecasting Tourism Demand wi…Data Analytics in the Supply Chain Management: Review of Machine Learning Applications in Demand Forecasting (2020)Data Analytics in the Supply …Daily tourism volume forecasting for tourist attractions (2020)Daily tourism volume forecast…A deep learning approach for daily tourist flow forecasting with consumer search data (2020)A deep learning approach for …Spatial-temporal forecasting of tourism demand (2019)Spatial-temporal forecasting …Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Statistical analysis of cointegration vectors (1988)MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY (1990)Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries (2007)CO2 emissions, electricity consumption and output in ASEAN (2010)The contribution of foreign direct investment to clean energy use, carbon emissions and economic growth (2013)Time Series Analysis, Forecasting and Control. 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(1978)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Tourism demand forecasting using tourist-generated online review data (2022)Tourism demand forecasting with spatiotemporal features (2022)Testing the equality of prediction mean squared errors (1997)Consumer Confidence and Consumer Spending (2004)Now-Casting and the Real-Time Data Flow (2013)In Search of Attention (2011)Text as Data (2019)Investor attention, index performance, and return predictability (2014)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2012)Applications of deep learning in stock market prediction: Recent progress (2021)Machine learning in the Chinese stock market (2021)
this work references cited by second hop

References

  • 1994Comparing Predictive Accuracy5,495 cited
  • 2012Predicting the Present with Google Trends2,353 cited
  • 1999Numerical distribution functions of likelihood ratio tests for cointegration2,028 cited
  • 2002Comparing Predictive Accuracy1,745 cited
  • 2007Tourism demand modelling and forecasting—A review of recent research1,419 cited
  • 1995Forecasting tourism demand: A review of empirical research896 cited
  • 2011Forecasting private consumption: survey-based indicators vs. Google trends560 cited
  • 2009Google Econometrics and Unemployment Forecasting439 cited
  • 2014Forecasting Chinese tourist volume with search engine data432 cited

Cited by

  • 2020Forecasting tourism demand with multisource big data260 cited
  • 2020Review of tourism forecasting research with internet data194 cited
  • 2020Daily tourism volume forecasting for tourist attractions183 cited
  • 2020Tourism Demand Forecasting: A Decomposed Deep Learning Approach179 cited
  • 2020Improving Tourist Arrival Prediction: A Big Data and Artificial Neural Network Approach165 cited
  • 2021A systematic literature review on the use of big data for sustainable tourism

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150 cited
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  • 2021Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making134 cited
  • 2021Using SARIMA–CNN–LSTM approach to forecast daily tourism demand130 cited
  • 2020Machine Learning in Internet Search Query Selection for Tourism Forecasting106 cited
  • 2019Spatial-temporal forecasting of tourism demand90 cited
  • 2024Tourism and Hospitality Forecasting With Big Data: A Systematic Review of the Literature86 cited
  • 2020Forecasting Tourism Demand with an Improved Mixed Data Sampling Model82 cited
  • 2022Does internet public participation slow down environmental pollution?77 cited
  • 2020A deep learning approach for daily tourist flow forecasting with consumer search data76 cited
  • 2021Forecasting crude oil price with a new hybrid approach and multi-source data73 cited