The image shaping of tourist attractions is one of the important factors to attract tourists. This paper explores the perceived impression of Fuzhou in tourists' mind and the perceived dimensions of tourists' attention by studying the review texts of tourists when they visit Fuzhou. By collecting reviews about Fuzhou on Tongcheng.com, Ctrip.com, and Donkey Mama, the destination image of Fuzhou is obtained through LDA (Latent Dirichlet Allocation) theme modeling model and SVM (Support Vector Machine) sentiment analysis model text data mining, so as to objectively extract the perceptual dimensions of tourists when visiting Fuzhou. The study found that the perceptual dimensions that tourists focus on during their visit to Fuzhou are mainly, namely, "tourism services," "entrance fee," "human landscape," "natural landscape;" "natural scenery," "history and culture," and "activity experience". The results of the study have some reference significance for Fuzhou in construction and promotion.
In recent years, data mining algorithms have been widely recognized as an important way to predict diseases. In the medical field, we are often faced with massive data. How to choose a model and improve the model to obtain better results is a problem that researchers are committed to solving. This paper starts with the classification model of Support Vector Machine, and optimizes the its parameters by processing the data. We used the previous Genetic Algorithm for comparing, and proposed an improved Genetic Algorithm to optimize the prediction of Support Vector Machine on the Coronary Heart Disease dataset. The experimental results show that the improved Genetic Algorithm has better prediction accuracy than the previous Genetic Algorithm.
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