Tourism activity recognition and discovery based on improved LDA model
Yifan Yuan, Junping Du, Jang Myung Lee · 2016
LDA (Latent Dirichlet Allocation) model is a kind of unsupervised learning model which can extract the hidden topic from text in recent years. In this paper, we proposed a novel LDA model based on the traditional LDA model, which is integrated into the information of text category (Activity-topic LDA). In this paper, the Activity-topic LDA is proposed to improve the original latent Dirichlet allocation (LDA) model. On the basis of the LDA, the proposed method adds the tourism activity information, and obtains the probability distribution model of the tourism activities. Based on this model, we can identify and discover the theme of tourism activities.