A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles.
Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extract words from article titles. The popularity measures of article titles are then analyzed by using the search indexes obtained from Google search engine. Backpropagation Neural Networks (BPNNs) have successfully been used to develop prediction models for sales forecasting. In this study, we propose a novel hybrid neural network model for sales forecasting based on the prediction result of time series forecasting and the popularity of article titles. The proposed model uses the historical sales data, popularity of article titles, and the prediction result of a time series, Autoregressive Integrated Moving Average (ARIMA) forecasting method to learn a BPNN-based forecasting model. Our proposed forecasting model is experimentally evaluated by comparing with conventional sales prediction techniques. The experimental result shows that our proposed forecasting method outperforms conventional techniques which do not consider the popularity of title words.
Institute of Information Management, National Chiao Tung University, Hsinchu 300, Taiwan; Computational Intelligence Technology Center, Industrial Technology Research Institute, Chutung, Hsinchu 310, Taiwan.
Hani
H
Omar
The University of Danang, Campus in Kon Tum, No. 129 Phan Dinh Phung Street, Kon Tum 580000, Vietnam.
Van Hai
VH
Hoang
Institute of Information Management, National Chiao Tung University, Hsinchu 300, Taiwan.
Duen-Ren
DR
Liu
D003132:Commerce / Q000639:trends*; D005544:Forecasting; D006801:Humans; D016247:Information Storage and Retrieval; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011642:Publications / Q000706:statistics & numerical data; D012044:Regression Analysis; D015203:Reproducibility of Results; D014825:Vocabulary