An image selection method for image representation of tourism destination based on comment text and image data

One of the challenges faced by Diffused Metal-Oxide Semiconductor (DMOs) is how to track the behavior of tourists and provide more comfortable experience for tourists. Nowadays, multi-source tourism big data provides many available information for improving tourists’ experience. For management organizations, in order to achieve better publicity effect, how to choose the appropriate image as the representative of the destination image has become a problem. Based on the review text and image data, this paper proposes a method, Scale-invariant feature transform KMeans (SIFT-KMeans) of selecting the representative image of tourism destination. This method uses the text and image data generated by tourists to carry out a series of analysis and processing, and then feeds back the results to tourists, so as to reflect the greatest interest of tourists. The accuracy and stability of this method is wonderful, and the change of destination image can be reflected through the change of time. The destination management organization can carry out corresponding construction and publicity based on the obtained results.