Analysis of rural tourism culture advertising content based on LSTM-CNN model

Rural culture has multiple values such as history, culture, economy and ecology, which needs to be protected using utilization and be utilized through protection, so as to realize living inheritance. Developing tourism industry is not only a significant force for rural revitalization, but also a vital path for living inheritance of rural culture. The recognition of rural tourism culture advertising content is an important part of natural language processing tasks. In recent years, generic named entity recognition models based on deep learning have achieved remarkable results. Whereas, in the field of tourism, the recognition of content of rural tourism culture advertising mainly depends on feature engineering. This paper proposes a network model based on Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). Escaping from using any artificial features, this model extracts and represents the local information features of the text through the neural network, and learns and uses the context information of the text to realize the recognition of rural tourism culture advertising content. The experimental results show that the method proposed in this paper can effectively recognize the content of rural tourism culture advertising.