Improved K-Means Algorithm for Finding Public Opinion of Mount Emei Tourism
Zhonghua Li, Liping Jia, Bingjun Su · 2019
Due to the rise of Mount Emei Tourism, more and more tourists express their travel thoughts, which will influence potential tourists. In this paper, relying on the data-crawling technology, public opinions of Mount Emei are crawled. After data cleaning, word-segmentation is used to build the word bags. Through contour coefficient, the number of cluster is determined. An improved K-means algorithm is proposed to cluster the public opinions. With the crawled data, the public opinions of Mount Emei is categorized into five cluster. The results show that the tourists are satisfied with the tourism in Mount Emei.