Abstract: Embodiments disclosed relate to a computer device and a method for predicting market demand of commodities. The method includes: creating multiple-sources data for each of a plurality of commodities, wherein each of the all multiple-sources data comes from a plurality data sources; storing the all multiple-sources data; extracting a plurality of features from a corresponding one of the all multiple-sources data for each of the commodities to build a feature matrix for each of the data sources; performing a tensor decomposition process on the feature matrices to produce at least one latent feature matrix; and performing a deep learning process on the at least one latent feature matrix to build a prediction model and predicting market demand of each of the commodities according to the prediction model.