Vertical Search Method of Tourism Information Based on Mixed Semantic Similarity

With the rapid development of the tourism industry, the volume of tourism information has increased exponentially, making it difficult for tourists to obtain the tourism information they need, which has become the main factor restricting the development of the tourism industry. In order to solve the above problems, the research on vertical search method of tourism information based on mixed semantic similarity is proposed. The Heritrix web crawler is used to collect tourism information and de duplicate it. On this basis, the Nutch structure is used to process tourism information, calculate the mixed semantic similarity between tourism information and known topics, and determine the corresponding topics of tourism information based on this, and develop an adaptive vertical search algorithm for tourism information. The vertical search results of tourism information can be obtained by executing the formulation algorithm. The experimental data shows that after the application of the proposed method, the maximum recall rate of vertical search of tourism information is 96%, the maximum precision rate of vertical search of tourism information is 98%, and the minimum response time of vertical search of tourism information is 0.56s, which fully proves that the proposed method has better application performance.