The combination of culture and tourism is becoming closer and closer, and in the process of tourism, how to make the public more convenient and accurate access to the relevant content of the culture accumulated for thousands of years is also a problem that all parties are trying to solve. In this paper, under the background of the widespread popularity of mobile terminals and the continuous enrichment of image and text data, the content-based image feature vector processing is carried out by convolutional neural network method, which is combined with the collected data set of cultural signs of tourist attractions to retrieve the main content of the image from identifying the main content. The applied system can be used as an image retrieval access of an image database of cultural attractions or cultural relics. The experimental results show that the average accuracy of the proposed algorithm is 77.6, which is better than other mainstream algorithms. As an important initial identification link, it can create conditions for the study of interest recommendation of cultural content and tourism path planning.
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